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
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-6, 8-10, 14, 15, 22-24, 26, 30, 31-34, 36-39 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081).
In regards to claim 1, Yu teaches a system for a host vehicle [e.g. the camera may be a camera of a vehicle incorporating the AR navigation system, c.3 L.46-59], the system comprising:
at least one processor [Fig. 3; e.g. processing unit, c.8 L.22-49] comprising circuitry [Fig. 3; e.g. processor, c.8 L.22-49] and a memory [Fig. 3; e.g. memory, c.8 L.22-49], wherein the memory includes instructions [Fig. 3; e.g. instructions, c.8 L.22-49] that when executed by the circuitry cause the at least one processor to:
receive at least one image captured by a camera of the host vehicle from an environment of the host vehicle [e.g. AR navigation system 100a receives an input image such as input image 100b. The input image 100b may be captured by a camera. The input image 100b approximates the current view of the real-world scene in the user's view (e.g., through the windshield of a vehicle while driving), c.3 L.46-67];
segment the at least one image, wherein segmenting the image includes identifying a first portion of the at least one image and a second portion of the at least one image, the first portion being different from the second portion [e.g. Segmentation image 100c may be a binary object mask image having pixels 110 set to a first common value (e.g., one) where roadway objects such as vehicle 104 are located in input image 100b, and having pixels 112 set to another common value (e.g., zero) elsewhere. The segmentation image is generated using artificial intelligence operations such as deep learning semantic segmentation operations, c.4 L.1-33];
augment the at least one image to include a representation of the augmented reality object, wherein the at least one augmented image includes a representation of the environment of the host vehicle and the representation of the augmented reality object [Fig. 1A; e.g. The segmentation image may be blended with an AR path overlay image to generate an object-masked AR path overlay image. The object-masked AR path overlay image may be blended with the input image to generate an output image, Abstract].
Yu does not explicitly teach
receive a point cloud generated based on an output of a LiDAR;
determine a location for an augmented reality object relative to the at least one image based on the first portion of the segmented image and at least a portion of the point cloud;
select or generate an augmented reality object; and
However, Gerrese teaches
receive a point cloud generated based on an output of a LiDAR [e.g. The sensor suite 102 includes LIDARs implemented using scanning LIDARs. Scanning LIDARs have a dynamically configurable field of view that provides a point-cloud of the region intended to scan. A live feed of camera images, LIDAR point clouds, radar feeds while the vehicle is driving, 0027, 0054];
select or generate an augmented reality object [e.g. An augmented reality image is generated based on the image analysis and perception system analysis. The perception system can be used, for example, to place objects with real world coordinates into 3D space, as well as to add filters, skins, and/or textures on top of existing objects, 0051].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Yu’s system with the features of
receive a point cloud generated based on an output of a LiDAR;
select or generate an augmented reality object
in the same conventional manner as taught by Gerrese because Gerrese provides an immersive in-vehicle experience with customizable virtual and augmented reality options [0004].
Yu as modified by Gerrese does not explicitly teach
determine a location for an augmented reality object relative to the at least one image based on the first portion of the segmented image and at least a portion of the point cloud.
However, Kentley-Klay teaches
determine a location for an augmented reality object relative to the at least one image based on the first portion of the segmented image and at least a portion of the point cloud [e.g. The augmented reality component 230 can receive image data, LIDAR data, radar data, and the like to determine a mesh of an environment onto which augmented reality elements can be projected. Augmented scenes can be created based on a known pose (position and orientation) so that artificial objects can be rendered with a proper perspective, c.8 L.9-47].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of
determine a location for an augmented reality object relative to the at least one image based on the first portion of the segmented image and at least a portion of the point cloud;
in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 2, Yu teaches the system of claim 1, wherein the first portion of the at least one image includes a representation of an object and the second portion of the at least one image includes a representation of a road surface [Fig. 1A; e.g. the segmentation image is a binary object mask image that separates roadway objects such as vehicle from any background pixels not on the road, road pixels, or pixels that indicate areas adjacent to the road, c.4 L.1-33].
In regards to claim 3, Yu teaches the system of claim 2, wherein the object includes a target vehicle [e.g. a vehicle 104 driving on the same roadway 102 as that of the user, c.3 L.60-67].
In regards to claim 4, Yu as modified by Gerrese does not explicitly teach the system of claim 3, wherein the target vehicle is at least partially occluded by another object.
However, Kentley-Klay teaches the system of claim 3, wherein the target vehicle is at least partially occluded by another object [e.g. augmented reality elements 704 for identifying a vehicle at least partially obscured by another object (e.g., a building 706), c.16 L.60-67].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein the target vehicle is at least partially occluded by another object in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 5, Yu teaches the system of claim 2, wherein the object includes a pedestrian [e.g. such as a pedestrian, c.4 L.29-33].
In regards to claim 6, Yu as modified by Gerrese does not explicitly teach the system of claim 5, wherein the pedestrian is at least partially occluded by another object.
However, Kentley-Klay teaches the system of claim 5, wherein the pedestrian is at least partially occluded by another object [e.g. the object such as a pedestrian is not visible to the user device because of one or more obstructions, c.17 L.6-8].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein the pedestrian is at least partially occluded by another object in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 8, Yu as modified by Gerrese does not explicitly teach the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to render the representation of the augmented reality object.
However, Kentley-Klay teaches the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to render the representation of the augmented reality object [e.g. augmented scenes can be created based on a known pose (position and orientation) so that artificial objects can be rendered with a proper perspective, c.8 L.19-23].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to render the representation of the augmented reality object in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 9, Yu does not explicitly teach the system of claim 8, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to select the representation of the augmented reality object from an image library.
However, Gerrese teaches the system of claim 8, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to select the representation of the augmented reality object from an image library [e.g. a pre-built 3D asset from a selected library containing texture maps and surface detail, 0056].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Yu’s system with the features of wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to select the representation of the augmented reality object from an image library in the same conventional manner as taught by Gerrese because Gerrese provides an immersive in-vehicle experience with customizable virtual and augmented reality options [0004].
In regards to claim 10, Yu does not explicitly teach the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to remove data associated with a portion of the at least one image that is occluded by the augmented reality object.
However, Gerrese teaches the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to remove data associated with a portion of the at least one image that is occluded by the augmented reality object [e.g. identifying a point in space and swapping out the point in space with a pre-built 3D asset, 0056].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Yu’s system with the features of wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to remove data associated with a portion of the at least one image that is occluded by the augmented reality object in the same conventional manner as taught by Gerrese because Gerrese provides an immersive in-vehicle experience with customizable virtual and augmented reality options [0004].
In regards to claim 14, Yu does not explicitly teach the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to cause the at least one augmented image to be output to a display device.
However, Gerrese teaches the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to cause the at least one augmented image to be output to a display device [e.g. the augmented data can be displayed through immersive interior window screens and surface projectors, 0059].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Yu’s system with the features of wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to cause the at least one augmented image to be output to a display device in the same conventional manner as taught by Gerrese because Gerrese provides an immersive in-vehicle experience with customizable virtual and augmented reality options [0004].
In regards to claim 15, Yu does not explicitly teach the system of claim 14, wherein the display device is a transparent display.
However, Gerrese teaches the system of claim 14, wherein the display device is a transparent display [e.g. the interior windows can become immersive interior window screens, and the windows can transform from transparent glass to opaque digital screens, 0059].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Yu’s system with the features of wherein the display device is a transparent display in the same conventional manner as taught by Gerrese because Gerrese provides an immersive in-vehicle experience with customizable virtual and augmented reality options [0004].
In regards to claim 22, Yu as modified by Gerrese does not explicitly teach the system of claim 1, wherein the augmented reality object is a representation of target vehicle.
However, Kentley-Klay teaches the system of claim 1, wherein the augmented reality object is a representation of target vehicle [e.g. the augmented reality element 704 can indicate a pose of the vehicle (e.g., as a three-dimensional representation of the vehicle), c.16 L.65-67].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein the augmented reality object is a representation of target vehicle in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 23, Yu as modified by Gerrese does not explicitly teach the system of claim 22, wherein at least a portion of the target vehicle is occluded by another object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the object occluding the at least a portion of the target vehicle.
However, Kentley-Klay teaches the system of claim 22, wherein at least a portion of the target vehicle is occluded by another object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the object occluding the at least a portion of the target vehicle [Fig. 7; e.g. The augmented reality element 704 can represent a portion of a vehicle that is obscured, while an unobscured portion of a vehicle can be represented by captured image data. In other words, the augmented reality element appears in front of the building occluding the portion of vehicle that is obscured, c.17 L.2-6].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein at least a portion of the target vehicle is occluded by another object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the object occluding the at least a portion of the target vehicle in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 24, Yu does not explicitly teach the system of claim 1, wherein the augmented reality object is a representation of an animal.
However, Gerrese teaches the system of claim 1, wherein the augmented reality object is a representation of an animal [e.g. a roar of a virtual animal visible in the augmented reality image, 0051].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Yu’s system with the features of wherein the augmented reality object is a representation of an animal in the same conventional manner as taught by Gerrese because Gerrese provides an immersive in-vehicle experience with customizable virtual and augmented reality options [0004].
In regards to claim 26, Yu as modified by Gerrese does not explicitly teach the system of claim 1, wherein the augmented reality object is a representation of a pedestrian.
However, Kentley-Klay teaches the system of claim 1, wherein the augmented reality object is a representation of a pedestrian [e.g. any augmented reality elements such as representations of a person, c.15 L.24-28].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein the augmented reality object is a representation of a pedestrian in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 27, Yu as modified by Gerrese does not explicitly teach the system of claim 26, wherein at least a portion of the pedestrian is occluded by a target object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the target object occluding the at least a portion of the pedestrian.
However, Kentley-Klay teaches the system of claim 26, wherein at least a portion of the pedestrian is occluded by a target object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the target object occluding the at least a portion of the pedestrian [Fig. 9; e.g. A building 906 can obscure an object of interest, such as the user 304 to be picked up by the vehicle. In other words, the augmented reality element of the user appears in front of the building, c.17 L.64-c.18 L.8].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein at least a portion of the pedestrian is occluded by a target object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the target object occluding the at least a portion of the pedestrian in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 30, Yu as modified by Gerrese does not explicitly teach the system of claim 1, wherein the at least one augmented image includes at least one augmented text description associated with the augmented reality object.
However, Kentley-Klay teaches the system of claim 1, wherein the at least one augmented image includes at least one augmented text description associated with the augmented reality object [e.g. Additional augmented reality elements 704 can include, but are not limited to, time and/or distance indications representing a time until a vehicle is scheduled to arrive at a pickup location or a distance between the user device and the vehicle, or the between the pickup location and the vehicle, c.17 L.18-22].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein the at least one augmented image includes at least one augmented text description associated with the augmented reality object in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 31, Yu as modified by Gerrese does not explicitly teach the system of claim 30, wherein the at least one augmented text description includes a label for the augmented reality object.
However, Kentley-Klay teaches the system of claim 30, wherein the at least one augmented text description includes a label for the augmented reality object [e.g. determining, based at least in part on the location of the vehicle, a portion of the first image data associated with the vehicle; and generating the computer-generated element to indicate an identity of the vehicle, c.27 L.29-32].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein the at least one augmented text description includes a label for the augmented reality object in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 32, the claim recites similar limitations as claim 1 but in the form of a non-transitory computer-readable medium storing program instructions executable by at least one processor to perform the steps of claim 1. Furthermore, Yu teaches a non-transitory computer-readable medium [e.g. computer readable storage medium, c.9 L.36-63] storing program instructions [e.g. instructions, c.9 L.36-63] executable by at least one processor [e.g. one or more processors, c.9 L.36-63] to perform the steps of claim 1. Therefore, the same rationale as claim 1 is applied.
In regards to claim 33, the claim recites similar limitations as claim 8. Therefore, the same rationale as claim 8 is applied.
In regards to claim 34, the claim recites similar limitations as claim 9. Therefore, the same rationale as claim 9 is applied.
In regards to claim 36, the claim recites similar limitations as claim 1 but in the form of a method. Therefore, the same rationale as claim 1 is applied.
In regards to claim 37, the claim recites similar limitations as claim 10. Therefore, the same rationale as claim 10 is applied.
In regards to claim 38, Yu as modified by Gerrese does not explicitly teach the method of claim 36, wherein at least a portion of the augmented reality object is occluded by another object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the object occluding the at least a portion of the augmented reality object.
However, Kentley-Klay teaches the method of claim 36, wherein at least a portion of the augmented reality object is occluded by another object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the object occluding the at least a portion of the augmented reality object [Fig. 7; e.g. The augmented reality element 704 can represent a portion of a vehicle that is obscured, while an unobscured portion of a vehicle can be represented by captured image data. In other words, the augmented reality element appears in front of the building occluding the portion of vehicle that is obscured, c.17 L.2-6].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese with the features of wherein at least a portion of the augmented reality object is occluded by another object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the object occluding the at least a portion of the augmented reality object in the same conventional manner as taught by Kentley-Klay because Kentley-Klay provides a method for capturing data by sensors of the vehicle and by sensors of a user device that can be used to orient a user within an environment, and/or provide visualizations or augmented reality elements to provide information and enrich a user experience [c.2 L.26-46].
In regards to claim 39, the claim recites similar limitations as claim 30. Therefore, the same rationale as claim 30 is applied.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081) as applied to claim 1 above, and further in view of Elangovan et al. (U.S. Patent 10,982,968).
In regards to claim 7, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 1, wherein the at least one image includes a video stream.
However, Elangovan teaches the system of claim 1, wherein the at least one image includes a video stream [e.g. the video data comprising a plurality of frames with each frame representing a scene from a route being navigated by the vehicle, c.29 L.64-c.30 L.15].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the at least one image includes a video stream in the same conventional manner as taught by Elangovan because video streams are well known and commonly used in the art of autonomous vehicle navigation systems.
Claim(s) 11-13, 35 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081) as applied to claims 1, 32 above, and further in view of Bogdoll et al. (U.S. Patent 11,455,565).
In regards to claim 11, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to input the augmented at least one image to a trained system.
However, Bogdoll teaches the system of claim 1, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to input the augmented at least one image to a trained system [e.g. training a machine learning model to detect obstacles according to the augmented point cloud, see claim 9 of Bogdoll].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to input the augmented at least one image to a trained system in the same conventional manner as taught by Bogdoll because Bogdoll provides an improved approach for generating scenarios from recorded sensor data by augmenting these with simulated sensor data [c.1 L.29-31].
In regards to claim 12, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 11, wherein the trained system includes one or more neural networks.
However, Bogdoll teaches the system of claim 11, wherein the trained system includes one or more neural networks [e.g. The machine learning model 118 may be a deep neural network, Bayesian network, or other type of machine learning model, c.2 L.61-c.3 L.2].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the trained system includes one or more neural networks in the same conventional manner as taught by Bogdoll because Bogdoll provides an improved approach for generating scenarios from recorded sensor data by augmenting these with simulated sensor data [c.1 L.29-31].
In regards to claim 13, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 12, wherein the trained system includes one or more machine learning models.
However, Bogdoll teaches the system of claim 12, wherein the trained system includes one or more machine learning models [e.g. machine learning model 118 trained using simulated sensor data generated according to the methods disclosed herein, c.2 L.61-c.3 L.2].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the trained system includes one or more machine learning models in the same conventional manner as taught by Bogdoll because Bogdoll provides an improved approach for generating scenarios from recorded sensor data by augmenting these with simulated sensor data [c.1 L.29-31].
In regards to claim 35, the claim recites similar limitations as claim 11. Therefore, the same rationale as claim 11 is applied.
Claim(s) 16, 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081) as applied to claims 1, 15 above, and further in view of Santos (U.S. Patent Application 20240010340).
In regards to claim 16, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 15, wherein the transparent display is a transparent organic light-emitting diode display.
However, Santos teaches the system of claim 15, wherein the transparent display is a transparent organic light-emitting diode display [e.g. the see-through display screen may include a transparent organic light-emitting diode display screen, 0043].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the transparent display is a transparent organic light-emitting diode display in the same conventional manner as taught by Santos because transparent organic light-emitting diode display are well known and commonly used in the art of computer display systems.
In regards to claim 25, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 1, wherein the augmented reality object is a representation of an advertisement.
However, Santos teaches the system of claim 1, wherein the augmented reality object is a representation of an advertisement [e.g. The database 402 may include advertisements which can be displayed associated with various of the POIs. For example, an advertisement can be displayed in AR view on the display device as text, graphical picture(s), video, etc. for a restaurant or other business corresponding to one of the POIs viewable to a passenger, 0040].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the augmented reality object is a representation of an advertisement in the same conventional manner as taught by Santos because Santos provides a method for innovative passenger experiences through the IFE system with dynamically changing content in a continuing effort to improve passenger satisfaction [0004].
Claim(s) 17, 18, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081) as applied to claim 15 above, and further in view of Seder et al. (U.S. Patent Application 20120089273).
In regards to claim 17, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 15, wherein the transparent display is positioned in front of at least a portion of a window of the host vehicle.
However, Seder teaches the system of claim 15, wherein the transparent display [e.g. transparent display, 0022] is positioned in front of at least a portion of a window of the host vehicle [e.g. windscreen of the vehicle, 0022].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the transparent display is positioned in front of at least a portion of a window of the host vehicle in the same conventional manner as taught by Seder because transparent displays such as heads up displays in front of the window are well known and commonly used in the art of vehicular display systems.
In regards to claim 18, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 17, wherein the window of the host vehicle is a front windshield.
However, Seder teaches the system of claim 17, wherein the window of the host vehicle is a front windshield [e.g. windscreen, 0022].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the window of the host vehicle is a front windshield in the same conventional manner as taught by Seder because front windshields are well known and commonly used in vehicular display systems.
In regards to claim 20, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 17, wherein the window of the host vehicle is a rear window of the host vehicle.
However, Seder teaches the system of claim 17, wherein the window of the host vehicle is a rear window of the host vehicle [e.g. rear window of the vehicle, 0013].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the window of the host vehicle is a rear window of the host vehicle in the same conventional manner as taught by Seder because rear windows are well known and commonly used in vehicular display systems.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081) and further in view of Seder et al. (U.S. Patent Application 20120089273) as applied to claim 15 above, and further in view of Santos (U.S. Patent Application 20240010340).
In regards to claim 19, Yu as modified by Gerrese, Kentley-Klay, and Seder does not explicitly teach the system of claim 17, wherein the window of the host vehicle is a side window of the host vehicle.
However, Santos teaches the system of claim 17, wherein the window of the host vehicle is a side window of the host vehicle [e.g. five digital aircraft windows along a side of an aircraft cabin, 0079].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese, Kentley-Klay, and Seder with the features of wherein the window of the host vehicle is a side window of the host vehicle in the same conventional manner as taught by Santos because side windows are well known and commonly used in the art of vehicular display systems.
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081) as applied to claim 1 above, and further in view of Harbach et al. (U.S. Patent Application 20160379411).
In regards to claim 21, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 1, wherein the augmented reality object is a representation of a gate.
However, Harbach teaches the system of claim 1, wherein the augmented reality object is a representation of a gate [e.g. augmented reality environment comprising virtual design elements such as barrier, 0026].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the augmented reality object is a representation of a gate in the same conventional manner as taught by Harbach because a representation of a gate is a well known virtual element on a roadway and they are commonly used in the art of augmented reality vehicle navigation systems.
Claim(s) 28, 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (U.S. Patent 10,495,476) in view of Gerrese et al. (U.S. Patent Application 20230306693) and further in view of Kentley-Klay et al. (U.S. Patent 10,809,081) as applied to claim 1 above, and further in view of Naserian et al. (U.S. Patent Application 20230133131).
In regards to claim 28, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 1, wherein the augmented reality object is a representation of a traffic light.
However, Naserian teaches the system of claim 1, wherein the augmented reality object is a representation of a traffic light [e.g. the graphical user interface is an augmented reality representation of a traffic signal indicative of the traffic signal cycle state and wherein the display is an augmented reality heads up display, 0015].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein the augmented reality object is a representation of a traffic light in the same conventional manner as taught by Naserian because Naserian provides a method for providing a traffic signal state information to a vehicle operator in order to warn the driver about conditions that may not be readily apparent [0002-0003].
In regards to claim 29, Yu as modified by Gerrese and Kentley-Klay does not explicitly teach the system of claim 28, wherein at least a portion of the traffic light is occluded by a target object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the target object occluding the at least a portion of the traffic light.
However, Naserian teaches the system of claim 28, wherein at least a portion of the traffic light is occluded by a target object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the target object occluding the at least a portion of the traffic light [Fig. 3; e.g. The traffic signal view obstruction is estimated in response to a portion of the leading vehicle being within a line of sight between the host vehicle and the traffic signal. The graphic 305 may be displayed in a location to the driver approximately where the traffic signal would be visible to the driver if not obstructed by the leading vehicle, 0011, 0049].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified the combination of Yu’s system and the teachings of Gerrese and Kentley-Klay with the features of wherein at least a portion of the traffic light is occluded by a target object in the environment of the host vehicle, and the augmented reality object appears in front of at least a portion of the target object occluding the at least a portion of the traffic light in the same conventional manner as taught by Naserian because Naserian provides a method for providing a traffic signal state information to a vehicle operator in order to warn the driver about conditions that may not be readily apparent [0002-0003].
Conclusion
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/ANDREW SHIN/Examiner, Art Unit 2612
/Said Broome/Supervisory Patent Examiner, Art Unit 2612
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