DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2 and 8-11 are rejected under 35 U.S.C. 103 as being unpatentable over Stemle et al. (US Pub No. 20180043229 A1) in view of Deangelis et al. (CA 2956821 A1).
Regarding Claim 1,
Stemle discloses A method for controlling a gimbal recorder to record a game, comprising: detecting motion information of moving objects in a moving object group and motion information of a target ball in the game, the moving objects comprising players of the game; (Stemle, [0007], [0052], discloses system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected)
determining group motion information of the moving object group according to the motion information of the moving objects; (Stemle, [0007], discloses a system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof; motion information (speed or velocity) of moving objects in group (players) and/or target ball (baseball) motion information are determined)
Stemle does not explicitly disclose determining transition information according to the group motion information of the moving object group and/or the motion information of the target ball; controlling at least one of orientation or shooting parameters of the gimbal recorder according to the transition information.
Deangelis discloses determining transition information according to the group motion information of the moving object group and/or the motion information of the target ball; (Deangelis, [0005-0006], discloses computer-implemented method is disclosed for determining a target situation in an athletic event. In one embodiment, positional information including the relative positions of a group of selected participants is initially received from a participant tracking system. Aggregate motion of the selected participants is detected in real-time using the positional information. The target situation is determined to have occurred when a change in the aggregate motion occurs in accordance with a predetermined characteristic during an initial time interval; a video feed of an event is annotated by receiving positional information indicating the position of a selected participant in the event from a tracking system. The path of travel of the participant is determined from the positional information, and graphical information indicating the path of travel, and information identifying the participant, is overlaid onto the video feed; [0119-0123], discloses translation of this information into a size-in-the-video-frame metric involves a series of calculations/transforms including determining a camera's field of view based on pan, tilt and zoom of a plane parallel to the lens, and correcting that field-of-view measurement based on the degree to which the field is not parallel to the lens (i.e., correcting for camera angle, relative to field). Once the field-of-view of the camera (e.g., camera 117) is calculated, then the position and size within that field of view is calculated for each of the location units (on players of interest) within the view. This calculation also corrects for the camera angle. Rather than use the raw noisy location data, both the field-of-view and the size-in-the-video-frame calculations are based on filtered location data. The filtering may be identical to that used in controlling the camera motion; one embodiment of the present system 100, the path of travel of a participant is automatically analyzed and displayed to evaluate the performance of a participant. Figure 7 is a flowchart showing exemplarysteps performed in evaluating a participant's performance. As shown inFigure 7, at step 705, the path of travel of one or more selected participants is determined. The distance traveled by the participant, and/or the participant's velocity may also be determined. At step 710, paths of travel for multiple players are compared to determine how well a particular player was able to perform during a given play (e.g., in avoiding players from an opposing team, or in 'covering' another player). In the case of officials, their paths show where the officials traveled during a particular play. This information may be helpful in evaluating an official's effectiveness; at step 715, one or more players whose path meets predetermined criteria is automatically highlighted on a graphic. For example, 'open' players (i.e., offensive players who are separated from all defensive players by a certain distance) or blocked players (i.e., those whose velocity during a certain time period is less than a minimum threshold and who are positioned in sufficiently close proximity to a player on the opposite team), by changing the color of these players as displayed on a graphic, which may also show the players' path of travel; graphic showing a path of travel may also show orientation of the participant(s), for example, the direction in which a quarterback or referee was facing. A graphic may automatically change configuration in response to a target situation, for example, a dashed line may be displayed during play and a solid line displayed at the end of play. 0123] In one embodiment, system 100 may control the imaging of an event at least partially in response to event characterization information 104. The system may automatically direct a robotic camera 117 to capture or 'cover' a target situation such as the beginning of a play, or when certain players are positioned within a predetermined distance of each other. For example, a camera may be automatically directed to cover an area of interest such as the line of scrimmage, a huddle, or a particular participant or participants in response to, or in anticipation of, a target situation, e.g., camera 117 may be directed to cover a quarterback upon detection of the beginning of a play. This procedure may help ensure that play is not missed due to other action on the field; motion of players is tracked (group of players by tracking their speed or velocity (change in speed transition in motion) or their positions and camera view (gimbal recorder) view is directed accordingly to adjust the view if there is specific change in event including huddle, scrimmage etc. to highlight the interest); group motion transition is determined based on seed or velocity change in group of players) and
controlling at least one of orientation or shooting parameters of the gimbal recorder according to the transition information. (Deangelis, [0119-0123], discloses translation of this information into a size-in-the-video-frame metric involves a series of calculations/transforms including determining a camera's field of view based on pan, tilt and zoom of a plane parallel to the lens, and correcting that field-of-view measurement based on the degree to which the field is not parallel to the lens (i.e., correcting for camera angle, relative to field). Once the field-of-view of the camera (e.g., camera 117) is calculated, then the position and size within that field of view is calculated for each of the location units (on players of interest) within the view. This calculation also corrects for the camera angle. Rather than use the raw noisy location data, both the field-of-view and the size-in-the-video-frame calculations are based on filtered location data. The filtering may be identical to that used in controlling the camera motion; one embodiment of the present system 100, the path of travel of a participant is automatically analyzed and displayed to evaluate the performance of a participant. Figure 7 is a flowchart showing exemplarysteps performed in evaluating a participant's performance. As shown inFigure 7, at step 705, the path of travel of one or more selected participants is determined. The distance traveled by the participant, and/or the participant's velocity may also be determined. At step 710, paths of travel for multiple players are compared to determine how well a particular player was able to perform during a given play (e.g., in avoiding players from an opposing team, or in 'covering' another player). In the case of officials, their paths show where the officials traveled during a particular play. This information may be helpful in evaluating an official's effectiveness; at step 715, one or more players whose path meets predetermined criteria is automatically highlighted on a graphic. For example, 'open' players (i.e., offensive players who are separated from all defensive players by a certain distance) or blocked players (i.e., those whose velocity during a certain time period is less than a minimum threshold and who are positioned in sufficiently close proximity to a player on the opposite team), by changing the color of these players as displayed on a graphic, which may also show the players' path of travel; graphic showing a path of travel may also show orientation of the participant(s), for example, the direction in which a quarterback or referee was facing. A graphic may automatically change configuration in response to a target situation, for example, a dashed line may be displayed during play and a solid line displayed at the end of play. 0123] In one embodiment, system 100 may control the imaging of an event at least partially in response to event characterization information 104. The system may automatically direct a robotic camera 117 to capture or 'cover' a target situation such as the beginning of a play, or when certain players are positioned within a predetermined distance of each other. For example, a camera may be automatically directed to cover an area of interest such as the line of scrimmage, a huddle, or a particular participant or participants in response to, or in anticipation of, a target situation, e.g., camera 117 may be directed to cover a quarterback upon detection of the beginning of a play. This procedure may help ensure that play is not missed due to other action on the field; motion of players is tracked (group of players by tracking their speed or velocity (change in speed transition in motion) or their positions and camera view (gimbal recorder) view is directed accordingly to adjust the view if there is specific change in event including huddle, scrimmage etc. to highlight the interest).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Stemle in view of Deangelis having a method of detecting motion of person(s) and target ball and tracking its position within a timeframe by tracking motion between sequential frames and detecting shift in motion data when significant event happens during a play or sports and highlight the event, with the teachings of Deangelis having, method of tracking motion data of group of people from their shift in motion data including change in speed or distance and determining the transition of the group location and adjusting camera position to capture the event in applications including highlighting interesting events in sports industry.
Regarding Claim 8,
The combination of Stemle and Deangelis further discloses determining ball transition information according to ball movement trajectory of the target ball in the multiple frames of images. (Stemle, [0007], [0052], discloses system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected). Additionally, the rational and motivation to combine the references Stemle and Deangelis as applied in rejection of claim 1 apply to this claim.
Regarding Claim 9,
The combination of Stemle and Deangelis further discloses identifying ball movement trajectory of the target ball according to the multiple frames of images; determining image critical positions in a ball reference image of the multiple frames of images; determining the ball transition direction according to the one of the image critical positions intersecting with the ball movement trajectory. (Stemle, [0007], [0052], discloses system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected). Additionally, the rational and motivation to combine the references Stemle and Deangelis as applied in rejection of claim 1 apply to this claim.
Regarding Claim 10,
The combination of Stemle and Deangelis further discloses identifying moving balls according to ball area trajectories in the multiple frames of images; determining the target ball from the moving balls according to a confidence that each of the moving balls belongs to a preset ball type; and determining the ball movement trajectory of the target ball from the ball area trajectories in the multiple frames of images. (Stemle, [0007], [0052], discloses system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected). Additionally, the rational and motivation to combine the references Stemle and Deangelis as applied in rejection of claim 1 apply to this claim.
Regarding Claim 11,
The combination of Stemle and Deangelis further discloses if the transition information is determined according to the group motion information of the moving object group, controlling one or more of a rotation direction, a rotation angle or a rotation speed of a gimbal supporting a recorder in the gimbal recorder according to a moving direction and moving speed of the moving object group; and if the transition information is determined according to the motion information of the target ball, controlling one or more of a rotation direction, a rotation angle or a rotation speed of the gimbal supporting the recorder in the gimbal recorder according to a moving direction and a movement speed of the target ball. (Stemle, [0007], [0052], discloses system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected). Additionally, the rational and motivation to combine the references Stemle and Deangelis as applied in rejection of claim 1 apply to this claim.
Claims 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Stemle as modified by Deangelis as applied, and further in view of Omari et al. (US Pub No. 20180204331-A1). The teachings of Stemle and Deangelis have been discussed previously.
Claims 12 and 13 recite device with elements and storage medium with
instructions corresponding to the method steps recited in Claim 11. Therefore, the
recited elements of the device claim 18 and instructions of storage medium claim 19 are
mapped to the proposed combination in the same manner as the corresponding steps
of Claim 11. Additionally, the rationale and motivation to combine the Gao and Lai
references presented in rejection of Claim 1, apply to these claims.
Omari discloses A gimbal, comprising: at least one memory to store a computer program; and at least one processor configured to, when executing the computer program (Omari, [0067-0068], FIG. 2D, discloses the imaging device 100 within the imaging device movement mechanism 30. The imaging device movement mechanism 30 couples the imaging device 100 to the movable platform 40. The implementation of the imaging device movement mechanism 30 shown in FIG. 2D is a three-axis gimbal mechanism that permits the imaging device 100 to be rotated about three independent axes. However, the imaging device movement mechanism 30 may include any type of translational and/or rotational elements that permit rotational and/or translational movement in one, two, or three dimensions; FIG. 3, which is a block diagram illustrating components of an imaging device 100 according to an implementation, the imaging device 100 may include a processor 132 which controls operation of the imaging device 100. In some implementations, the processor 132 may include a system on a chip (SOC), microcontroller, microprocessor, CPU, DSP, ASIC, GPU, and/or other processors that control the operation and functionality of the imaging device 100. The processor 132 may interface with mechanical, electrical, sensory, or power modules and/or a UI module 146 via driver interfaces and/or software abstraction layers. Additional processing and memory capacity may be used to support these processes. These components may be fully controlled by the processor 132. In some implementation, one or more components may be operable by one or more other control processes (e.g., a GPS receiver may include a processing apparatus configured to provide position and/or motion information to the processor 132 in accordance with a given schedule (e.g., values of latitude, longitude, and elevation at 10 Hz)); gimbal is disclosed).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Stemle and Deangelis method of tracking motion data of group of people from their shift in motion data including change in speed or distance and determining the transition of the group location and adjusting camera position to highlighting interesting events in sports, with the teachings of Omari having, gimbal having stabilizer or motor and/or handheld stand to hold camera device to stabilize motion of camera and steer the camera device in direction of interest.
Omari further discloses A gimbal recorder, comprising: a recorder to capture a video of a game; a gimbal to control orientation and/or shooting parameters of the recorder; at least one memory to store a computer program; and at least one processor configured to, when executing the computer program (Omari, [0018-0020], discloses movable imaging system includes a movable platform, an imaging device, and a tracking system. The movable platform is movable in real space. The imaging device is for capturing successive image frames that form a video, and is connected to the movable platform. The tracking system is for tracking a subject in the successive image frames. The tracking system locates a region of interest for a subsequent image frame at a predicted frame location of the subject in a future image frame. The predicted frame location is based on previous frame positions of the subject in the successive images, motion information of the imaging device, and motion information of the subject. The tracking system processes the region of interest of the future image frame to locate the subject in the future image frame; a method is provided for controlling a movable imaging assembly having a movable platform and an imaging device coupled to and movable relative to the movable platform. The method includes receiving user inputs that define an MIA position relative to a target and a frame position of the target within image frames captured by the imaging device. The user inputs include a horizontal distance, a circumferential position, and a horizontal distance that define the MIA position, and include a horizontal frame position and a vertical frame position that define the frame position. The method further includes predicting a future position of the target for a future time, and moving the MIA to be in the MIA position at the future time and moving the imaging device for the target to be in the frame position for an image frame captured at the future time; a method is provided for controlling a movable imaging assembly having a movable platform and an imaging device coupled to and movable relative to the movable platform. The method includes receiving user inputs that define an MIA position relative to a target and a frame position of the target within image frames captured by the imaging device. The method further includes predicting a future position of the target for a future time, and moving the MIA to be in the MIA position at the future time and moving the imaging device for the target to be in the frame position for an image frame captured at the future time). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Regarding Claim 14,
The combination of Stemle and Deangelis further discloses wherein the controlling at least one of the orientation or shooting parameters of the recorder according to the transition information comprises: if the transition information is determined according to the group motion information of the moving object group, controlling at least one or more of a rotation direction, a rotation angle or a rotation speed of the gimbal according to a moving direction and moving speed of the moving object group; and if the transition information is determined according to the motion information of the target ball, controlling at least one or more of a rotation direction, a rotation angle or a rotation speed of the gimbal according to a moving direction and a movement speed of the target ball. (Stemle, [0007], [0052], discloses system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Regarding Claim 15,
The combination of Stemle and Deangelis further discloses wherein the group motion information of the moving object group is determined according to optical flow displacement of each of multiple frames of images captured by the recording device. (Stemle, [0063], discloses the application provides a video system and method for tracking and imaging a thrown baseball as it moves in a first direction toward a throwing target. An algorithm is used to track the baseball and predict its position in subsequent video image frames. The predicted position of the baseball is used to narrow the search for the position of the baseball in subsequent frames. The predicted position of the baseball is also used when the baseball cannot be detected in certain video frames. As a pitched baseball approaches a target, an algorithm is employed to track the baseball including any change in travel direction and/or velocity. In particular, the position and motion of the baseball may be analyzed in more detail to detect if the baseball (a) hits the ground and bounces off the ground before reaching the throwing target; (b) hits the throwing target frame, if any, and bounces back in a direction opposite the first direction; (c) misses the throwing target completely; or (d) hits the throwing target whereby the zone(s) contacted by the baseball are detected and reported electronically; moving object trajectory is tracked since frame one to incoming sequential frames and their motion data including speed, velocity, direction or distance shift is determined by comparing the motion data between the consecutive frames). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Regarding Claim 16,
The combination of Stemle and Deangelis further discloses wherein the group motion information of the object group is determined according to a multi-target tracking method. (Stemle, [0007], [0052], [0063], discloses the application provides a video system and method for tracking and imaging a thrown baseball as it moves in a first direction toward a throwing target. An algorithm is used to track the baseball and predict its position in subsequent video image frames. The predicted position of the baseball is used to narrow the search for the position of the baseball in subsequent frames. The predicted position of the baseball is also used when the baseball cannot be detected in certain video frames. As a pitched baseball approaches a target, an algorithm is employed to track the baseball including any change in travel direction and/or velocity. In particular, the position and motion of the baseball may be analyzed in more detail to detect if the baseball (a) hits the ground and bounces off the ground before reaching the throwing target; (b) hits the throwing target frame, if any, and bounces back in a direction opposite the first direction; (c) misses the throwing target completely; or (d) hits the throwing target whereby the zone(s) contacted by the baseball are detected and reported electronically; system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected); multiple objects motion is tracked between frames (multitarget tracking); moving object trajectory is tracked since frame one to incoming sequential frames and their motion data including speed, velocity, direction or distance shift is determined by comparing the motion data between the consecutive frames). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Regarding Claim 17,
The combination of Stemle and Deangelis further discloses wherein the transition information is determined according to ball movement trajectory of the target ball in multiple frames of images captured by the recorder. (Stemle, [0007], [0052], [0063], discloses the application provides a video system and method for tracking and imaging a thrown baseball as it moves in a first direction toward a throwing target. An algorithm is used to track the baseball and predict its position in subsequent video image frames. The predicted position of the baseball is used to narrow the search for the position of the baseball in subsequent frames. The predicted position of the baseball is also used when the baseball cannot be detected in certain video frames. As a pitched baseball approaches a target, an algorithm is employed to track the baseball including any change in travel direction and/or velocity. In particular, the position and motion of the baseball may be analyzed in more detail to detect if the baseball (a) hits the ground and bounces off the ground before reaching the throwing target; (b) hits the throwing target frame, if any, and bounces back in a direction opposite the first direction; (c) misses the throwing target completely; or (d) hits the throwing target whereby the zone(s) contacted by the baseball are detected and reported electronically; system, including (1) one or more targets each target having an outlay of distinct zones; (2) one or more objects to be directed toward one or more targets; and (3) a computer vision system operationally configured to receive input providing the outlay of one or more particular targets; receive input providing one or more locations on one or more of the particular targets intended to be contacted by one or more objects; receive input providing motion information for one or more objects directed toward one or more targets; receive input providing the location that each of the one or more objects contacts a particular target; compute said received input to provide information related to accuracy, object velocity, object travel path, object vertical displacement, and combinations thereof.vision algorithms operationally configured to detect velocity, i.e., estimate travel speed of an object in space, vertical displacement and actual location of a propelled object. In baseball terms, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a pitched baseball. Moreover, vision algorithms are operationally configured to detect the velocity, vertical displacement and actual location of a particular pitched baseball in or around a known strike zone and compare the measured velocity, vertical displacement and actual location of the pitched baseball to the intended velocity, vertical displacement and intended location for that particular pitch; velocity (motion data) of moving baseball (target ball) is detected); multiple objects motion is tracked between frames (multitarget tracking); moving object trajectory is tracked since frame one to incoming sequential frames and their motion data including speed, velocity, direction or distance shift is determined by comparing the motion data between the consecutive frames). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Regarding Claim 18,
The combination of Stemle and Deangelis further discloses wherein the gimbal comprises a handheld portion and a gimbal portion, wherein the gimbal portion is disposed on the handheld portion. (Omari, [0198], discloses types of control discussed above may be applied even when a controllable UAV is not used as part of the MIA 20. For example, when the imaging device 100 is connected to the imaging device movement mechanism 30, such as the gimbal mechanism discussed above, but there is no movable platform 40 or it is not one that is remotely controllable (e.g., a downhill skier uses the imaging device 100 with the imaging device movement mechanism 30 mounted to the skier's helmet or handheld by the skier), various types of the voice commands 750, such as subject selection and the like may still be utilized; gimbal, handheld portion are disclosed). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Regarding Claim 19,
The combination of Stemle and Deangelis further discloses wherein the handheld portion comprises buttons for controlling the orientation and shooting parameters of the recorder. (Omari, [0198], discloses types of control discussed above may be applied even when a controllable UAV is not used as part of the MIA 20. For example, when the imaging device 100 is connected to the imaging device movement mechanism 30, such as the gimbal mechanism discussed above, but there is no movable platform 40 or it is not one that is remotely controllable (e.g., a downhill skier uses the imaging device 100 with the imaging device movement mechanism 30 mounted to the skier's helmet or handheld by the skier), various types of the voice commands 750, such as subject selection and the like may still be utilized; gimbal, handheld portion are disclosed). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Regarding Claim 20,
The combination of Stemle and Deangelis further discloses wherein the recorder is a mobile phone or a camera. (Deangelis [0023], discloses a method automatically captures an image of a location upon request, and includes the steps of: receiving a request from a requestor to capture the image of the location; determining an optimal camera for capturing the image of the location from at least one motorized camera; controlling the optimal camera to include the location within its field of view; capturing the image using the optimal camera, and delivering the image to the requestor; camera to record video or capture images is disclosed). Additionally, the rational and motivation to combine the references Stemle, Deangelis and Omari as applied in rejection of claim 12 apply to this claim.
Allowable Subject Matter
Claims 2, 3, 4, 5, 6 and 7 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
CA-3120303-A1 (Schwartz et al., process to partition a video feed to segment live player activity includes receiving, on a first recurring basis, a transmission of a central video feed from a first camera. The central video feed is calibrated against a spatial region represented in at least two dimensions that is encompassed by the central video feed. The process includes receiving, on a second recurring basis, a respective time-stamped position information from each tracking device in a plurality of tracking devices. Each tracking device is worn by a corresponding subject on the spatial region and transmits positional information that describes a time-stamped position of the corresponding subject in the spatial region. The process uses the received information and the calibration to define a first sub-view of the central video feed associated with a first subject. The first sub-view comprises a corresponding sub-frame associated with the first subject, Abstract).
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/Pinalben Patel/Examiner, Art Unit 2673
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