DETAILED ACTION
Specification
The disclosure is objected to because of apparent editorial/clerical errors. Going forward with examination, the following paragraphs are interpreted to be (Note that in applicant’s response, where a change is requested in the specification, an entire paragraph of the specification containing the change will be needed):
--[0029] FIG. 1B shows a back side of the acoustic imaging device 100. As shown, the device includes display 120, which can present image or other data. In some examples, display 120 comprises a touch screen display. The acoustic imaging device 100 includes a speaker 122, which can provide audio feedback signals to a user, and a wireless interface 124, which can enable wireless communication between the acoustic imaging device 100 and an external device. The device further includes controls 126, which can include one or more buttons, knobs, dials, switches, or other interfacing components to enable a user to interface with the acoustic imaging device 100. In some examples, controls 126 and a touchscreen display combine to provide a user interface of the acoustic imaging device 100.--
--[0040] During use of acoustic analysis system 200, processor 212 can control visible light camera module 206 to generate visible light data from a captured target scene for creating a visible light image. The visible light data may include luminosity data indicative of the color(s) associated with different portions of the captured target scene and/or the magnitude of light associated with different portions of the captured target scene. Processor 212 can generate a “frame” of visible light image data by measuring the response of each visible light sensor element of acoustic analysis system 200 a single time. By generating a frame of visible light data, processor 212 captures visible light image of a target scene at a given point in time. Processor 212 may also repeatedly measure the response of each visible light sensor element of acoustic analysis system 200 so as to generate a dynamic visible light image (e.g., a video representation) of a target scene. In some examples, the visible light camera module 206 may include its own dedicated processor or other circuitry (e.g., ASIC) capable of operating the visible light camera module 206. In some such embodiments, [[the]] a dedicated processor is in communication with processor 212 for providing visible light image data (e.g., RGB image data) to processor 212. In alternative embodiments, [[a]] the dedicated processor for the visible light camera module 206 may be integrated into processor 212.--
--[0067] FIGS. 3A-3C provide exemplary acoustic sensor array configurations, however other acoustic sensor array configurations may be used. Acoustic sensor array configurations may comprise a variety of shapes and patterns, such as acoustic sensors arranged in a grid-like pattern, in concentric circles, in a sunflower array, in an ordered circular array, or the like. FIG. 3D provides an exemplary embodiment wherein acoustic sensors 395 are arranged in an ordered circular array configuration. The ordered circular array, such as shown in FIG. 3D, may provide various distances between the acoustic sensors rather than having a uniform distance between the them. Such a configuration may help the acoustic sensor array discern a larger range of frequencies by using various portions of the acoustic sensor array. For example, more closely spaced acoustic sensors may be more effective at detecting higher frequencies; similarly, acoustic sensors spaced farther apart may be more effective at detecting lower frequencies. Thus, having a variety of distances between acoustic sensors, some closer and some farther, may help provide better detection for a larger range of frequencies. Furthermore, the ordered circular array of FIG. 3D may provide differences in time of arrival versus the location of sound for different portions of the array and thus help with focusing the acoustic sensor array and/or determining where an acoustic signal is being emitted from. Additionally, the ordered circular array may help resolve spatial aliasing and sidelobes compared to, for example, a rectangular array.--
Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Aoyanagi (JP 2010232888 A. This Office action provides a machine translation of Aoyanagi).
Aoyanagi teaches:
An acoustic analysis system 1 comprising (See figs. 1, 7B, 5A, 10B, reproduced below):
an acoustic sensor array (= microphone array 20) configured to receive acoustic (sound) signals from a target scene (having a sound source being, e.g., a person clapping hands or walking, as shown in fig. 5A or fig. 10B, respectively) and output acoustic data based on the acoustic signals (Abstract);
one or more processors (comprising an acoustic processing unit 30, an abnormal sound determination unit 40, a sound source position calculation unit 50, an image combination unit 60, an alarm processing unit 70, and a network processing unit 80) in communication with the acoustic sensor array 20 (as shown in fig. 1), wherein the one or more processors are configured to:
receive the acoustic data (being the sound signals from the sound source) from the acoustic sensor array (20);
identify a plurality of portions (to form an image) of the target scene (having the sound source) based on the acoustic data (by using a camera 10 in communication with the acoustic sensor array 20. The camera 10 may capture the plurality of portions – as shown in fig. 7B – to form the image of the target scene; Abstract);
associate respective acoustic profiles (which may be an envelope profile including sound level, frequency, number of occurrences, duration, and/or the like, of the sound signals; Pars. 26, 45-46) with the plurality of portions of the target scene (as shown, for example, in fig. 5B in which a person is clapping his hands; or as shown in fig. 10B in which a person is walking) is associated with the plurality of portions of the target scene; and
generate a display image (Figs. 7, 5A, 10B) having the plurality of portions of the target scene, wherein the acoustic data is visually represented profiles (as a small disk-shaped mark shown in fig. 5A; or marks a, b, c, d, e shown in fig. 10B) in the plurality of portions of the target scene according to the respective acoustic profiles (of respective clapping hands or footsteps; Pars. 42; 67-69).
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2. The acoustic analysis system of claim 1, wherein at least one acoustic profile (e.g., of the clapping hands) of the respective acoustic profiles differs from another acoustic profile (e.g., of the footsteps) in one or more acoustic criteria (e.g., sound level, frequency, and/or the like, as the sound of the clapping hands may differ from the sound of the footsteps by sound level, frequency, and/or the like. For instance, it appears that the person shown in fig. 10B may be clapping his hand while walking. The one or more processors appear able to differentiate the sound of the clapping hands from the sound of the footsteps based on sound level, frequency, and/or the like; Pars. 0026, 0045-0046).
3. The acoustic analysis system of claim 1, wherein respective boundaries of the plurality of portions of the target scene are represented in the display image (as shown in fig. 7B for example).
4. The acoustic analysis system of claim 1, wherein the plurality of portions of the target scene are identified based on one or more of:
locations of the acoustic signals in the target scene (as shown in figs. 5A, 10B),
acoustic parameters of the acoustic signals in the target scene,
a direction of an object (the person) within the target scene relative to the acoustic analysis system (as is evident from figs. 5A, 10B), or
one or more features or objects (e.g., the person clapping his hand, or walking) identified in the target scene (as shown in figs. 5A, 10B).
5. The acoustic analysis system of claim 1, wherein the one or more processors are configured to define at least one acoustic profile (e.g., of the clapping hands or footsteps) associated with at least one portion of the target scene based on one or more parameters (e.g., sound level and/or frequency. See discussion in claim 2).
6. The acoustic analysis system of claim 1, wherein an alarm profile (which is determined to be abnormal), is associated with a portion of the target scene, the alarm profile comprising acoustic criteria (e.g., sound level) that, when met by an acoustic signal (sound level) in the portion of the target scene, the acoustic analysis system is configured to notify an alarm condition (via the alarm processing unit 70; Fig. 1; Pars. 0032, 0073-0077).
7. The acoustic analysis system of claim 1, wherein acoustic data in different portions of the target scene are represented differently in the display image according to different acoustic criteria in the respective acoustic profiles (For instance, as discussed in claim 2, the person shown in fig. 10B may be clapping his hands while walking. The one or more processors appear able to differentiate the hand clapping sound from the waking sound based on the sound level, frequency, and/or the like. The acoustic data may be represented differently as a small disk-shaped mark shown in fig. 5A for the hand clapping sound and marks a, b, c, d, e shown in fig. 10b for the walking sound. Furthermore, the acoustic data may be represented differently in luminance value, color, shape, etc., in the display image according to different acoustic criteria in the respective acoustic profiles; Pars. 31, 49).
8. The acoustic analysis system of claim 1, wherein a respective acoustic profile includes periodicity criteria (= number of occurrences; Pars. 26, 45-46), and in the portion of the target scene associated with the respective acoustic profile, acoustic data representing acoustic signals that do not meet the periodicity criteria (e.g., more or less than the number of occurrences) are not represented or are visually represented different from acoustic data representing acoustic signals that meet the periodicity criteria (since the acoustic data representing acoustic signals that do not meet the periodicity criteria are determined to be not abnormal. For instance, there are many cases where it should be determined that constant motor sounds and/or wind noises associated with operation of an air conditioner are not abnormal sounds. However, when similar sound is generated for a moment or its level changes suddenly, it may be determined that the sound is not associated with the air conditioner operation but an abnormal sound; Pars. 32, 73-77).
9. The acoustic analysis system of claim 1, wherein a respective acoustic profile has frequency criteria, and in the portion of the target scene associated with the respective acoustic profile (frequency profile), acoustic data representing acoustic signals that do not meet the frequency criteria are not represented or are visually represented different from acoustic data representing acoustic signals that meet the frequency criteria (since the acoustic data representing acoustic signals that do not meet the frequency criteria are determined to be not abnormal. Evidently, such acoustic data may be, for example, motor sound, wind noise having respective frequency profile associated with operation of an air conditioner, for example; Pars. 32, 73-78).
10. The acoustic analysis system of claim 1, wherein a respective acoustic profile has an intensity criteria (= sound level), and in the portion of the target scene associated with the respective acoustic profile, acoustic data representing acoustic signals that do not meet the intensity criteria are not represented or are visually represented different from acoustic data representing acoustic signals that meet the intensity criteria (since the acoustic data representing acoustic signals that do not meet the periodicity criteria are determined to be not abnormal. For instance, as discussed in claim 8, there are many cases where it should be determined that constant motor sounds and/or wind noises associated with operation of an air conditioner are not abnormal sounds. However, when similar sound is generated for a moment or its level changes suddenly, it may be determined that the sound is not associated with the air conditioner operation but an abnormal sound; Pars. 32, 73-77).
11. The acoustic analysis system of claim 1, wherein a respective acoustic profile comprises an acoustic signature (of an abnormal sound profile that doesn’t match a normal sound profile), and in the portion of the target scene associated with the respective acoustic profile, acoustic data representing acoustic signals (normal sound signals) that do not match the acoustic signature (of the abnormal sound profile) are not represented or are visually represented different from acoustic data representing acoustic signals that match the acoustic signature (Pars. 0073-0078).
12. (essentially equivalent to claim 1 + claim 2)
A system that necessitates a method of acoustic analysis, comprising:
receiving acoustic data from an acoustic sensor array (20), wherein the acoustic data represents acoustic (sound) signals in a target scene (having a sound source being, e.g., a person clapping hands or walking, as shown in fig. 5A or fig. 10B, respectively);
identifying a plurality of portions (to form an image) of the target scene (having the sound source) based on the acoustic data (by using a camera 10 in communication with the acoustic sensor array 20. The camera 10 may capture the plurality of portions – as shown in fig. 7B – to form the image of the target scene; Abstract);
associating respective acoustic profiles (which may be an envelope profile including sound level, frequency, number of occurrences, duration, and the like, of the sound signals; Pars. 26, 45-46) with the plurality of portions of the target scene (as shown, for example, in fig. 5B in which a person is clapping his hands; or as shown in fig. 1B in which a person is walking) is associated with the plurality of portions of the target scene, wherein at least one acoustic profile (e.g. of the clapping hands) differs from another acoustic profile (e.g., of the footsteps) in one or more acoustic criteria (e.g., sound level and/or frequency, as the sound of the clapping hands may differ from the sound of the footsteps by sound level, frequency, and/or the like. For instance, it appears that the person shown in fig. 10B may be clapping his hands while walking. The one or more processors appear able to differentiate the sound of the clapping hands from the sound of the footsteps based on sound level, frequency, and/or the like; Pars. 0026, 0045-0046); and
generating a display image (Figs. 7, 5A, 10B) having the plurality of portions of the target scene, wherein the acoustic data is visually represented (as a small disk-shaped mark shown in fig. 5A; or marks a, b, c, d, e shown in fig. 10B) in the plurality of portions of the target scene according to the respective acoustic profiles (of the respective clapping hands or footsteps; Pars. 42; 67-69).
13. (essentially equivalent to claim 4)
The method of acoustic analysis of claim 12, wherein the plurality of portions of the target scene are identified based on one or more of:
locations of the acoustic signals in the target scene (as shown in figs. 5A, 10B),
acoustic parameters of the acoustic signals in the target scene,
a direction of an object (the person) within the target scene relative to the acoustic sensor array, or
one or more features or objects identified in the target scene. (e.g., the person clapping his hand, or walking) identified in the target scene (as shown in figs. 5A, 10B).
14. (essentially equivalent to claim 6)
The method of acoustic analysis of claim 12, wherein a respective acoustic profile (which is determined to be abnormal) includes alarm criteria, the method further comprising notifying an alarm condition when an acoustic signal in the portion of the target scene associated with the respective acoustic profile satisfies the alarm criteria (via the alarm processing unit 70; Fig. 1; Pars. 0032, 0073-0077).
15. (essentially equivalent to claim 8)
The method of acoustic analysis of claim 12, wherein a respective acoustic profile includes acoustic criteria comprising one or more of periodicity criteria, frequency criteria, intensity criteria, or an acoustic signature, and in the portion of the target scene associated with the respective acoustic profile, acoustic data representing acoustic signals that do not meet the acoustic criteria are not represented or are visually represented different than acoustic data representing acoustic signals that meet the acoustic criteria (since the acoustic data representing acoustic signals that do not meet the periodicity criteria, for example, are determined to be not abnormal. For instance, there are many cases where it should be determined that constant motor sounds and/or wind noises associated with operation of an air conditioner are not abnormal sounds. However, when similar sound is generated for a moment or its level changes suddenly, it may be determined that the sound is not associated with the air conditioner operation but an abnormal sound; Pars. 32, 73-77).
16. (essentially equivalent to claim 1)
An acoustic analysis system comprising:
one or more processors (comprising an acoustic processing unit 30, an abnormal sound determination unit 40, a sound source position calculation unit 50, an image combination unit 60, an alarm processing unit 70, and a network processing unit 80) configured to operate according to executable instructions, wherein in response to execution, the instructions cause the one or more processors to:
receive acoustic data representing acoustic signals in a target scene (wherein an acoustic sensor array 20 is configured to receive acoustic/sound signals from the target scene having a sound source being, e.g., a person clapping hands or walking, as shown in fig. 5A or fig. 10B, respectively);
identify a plurality of portions (to form an image) of the target scene (having the sound source) based on the acoustic data (wherein a camera 10 in communication with the acoustic sensor array 20 may capture the plurality of portions – as shown in fig. 7B – to form the image of the target scene; Abstract);
associate respective acoustic profiles (which may be an envelope profile including sound level, frequency, number of occurrences, duration, and/or the like, of the sound signals; Pars. 26, 45-46) with the plurality of portions of the target scene (as shown, for example, in fig. 5B in which a person is clapping his hands; or as shown in fig. 10B in which a person is walking) is associated with the plurality of portions of the target scene; and
generate a display image of the target scene (Figs. 7, 5A, 10B) in which the acoustic data is visually represented (as a small disk-shaped mark shown in fig. 5A; or marks a, b, c, d, e shown in fig. 10B) in the plurality of portions of the target scene according to the respective acoustic profiles (of the respective clapping hands or footsteps; Pars. 42; 67-69).
17. (essentially equivalent to claim 2)
The acoustic analysis system of claim 16, wherein at least one acoustic profile (e.g., of the clapping hands) of the respective acoustic profiles differs from another acoustic profile (e.g., of the footsteps) in one or more acoustic criteria (e.g., sound level, frequency, and/or the like, as the sound of the clapping hands may differ from the sound of the footsteps by sound level, frequency, and/or the like. For instance, it appears that the person shown in fig. 10B may be clapping his hand while walking. The one or more processors appear able to differentiate the sound of the clapping hands from the sound of the footsteps based on sound level, frequency, and/or the like; Pars. 0026, 0045-0046).
18. (essentially equivalent to claim 6)
The acoustic analysis system of claim 16, wherein the instructions cause the one or more processors to associate an alarm profile (which is determined to be abnormal) with a portion of the target scene, the alarm profile (which is determined to be abnormal) comprising acoustic criteria (e.g., sound level) that, when met by an acoustic signal (sound level) in the portion of the target scene, the acoustic analysis system is configured to notify an alarm condition (via an alarm processing unit 70; Fig. 1; Pars. 0032, 0073-0077).
19. (essentially equivalent to claim 7)
The acoustic analysis system of claim 16, wherein acoustic data in different portions of the target scene are represented differently in the display image according to different acoustic criteria in the respective acoustic profiles (See discussion in claim 7).
20. (essentially equivalent to claims 8-10)
The acoustic analysis system of claim 16, wherein a respective acoustic profile includes acoustic criteria comprising one or more of periodicity criteria, frequency criteria, intensity criteria, or an acoustic signature, and in the portion of the target scene associated with the respective acoustic profile, acoustic data representing acoustic signals that do not meet the acoustic criteria are not represented or are visually represented different than acoustic data representing acoustic signals that meet the acoustic criteria (since the acoustic data representing acoustic signals that do not meet the periodicity criteria are determined to be not abnormal. See discussions in claims 8-10).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nguyen (Wyn) Q. Ha whose telephone number is (571) 272-2863, email: nguyeq.ha@uspto.gov. The examiner can normally be reached Monday - Friday 8 am - 4:30 pm (Eastern Time).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen Meier can be reached at (571) 272-2149. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Nguyen Q. Ha/Primary Examiner, Art Unit 2853 September 27, 2026
