Method and System for Approximating Deep Neural Networks for Anatomical Object Detection
US-2016328643-A1 · Nov 10, 2016 · US
US9769367B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9769367-B2 |
| Application number | US-201615048360-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 19, 2016 |
| Priority date | Aug 7, 2015 |
| Publication date | Sep 19, 2017 |
| Grant date | Sep 19, 2017 |
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The present disclosure relates to a method for controlling a digital photography system. The method includes obtaining, by a device, image data and audio data. The method also includes identifying one or more objects in the image data and obtaining a transcription of the audio data. The method also includes controlling a future operation of the device based at least on the one or more objects identified in the image data, and the transcription of the audio data.
Opening claim text (preview).
What is claimed is: 1. A computer-implemented method comprising: obtaining, by a computing device operable to capture images, (i) image data that describes a first scene and (ii) audio data; identifying, by the computing device, one or more objects in the first scene based on the image data; obtaining, by the computing device, a transcription of a human speech utterance described by the audio data, wherein the human speech utterance refers to at least a first object of the one or more objects included in the first scene; identifying, by the computing device based at least in part on the transcription and based at least in part on the image data, at least the first object that is referred to by the human speech utterance; defining, by the computing device, a new rule that specifies an image capture behavior of the computing device in response to future instances of identification of the first object in future image data that is different than the current image data; and controlling, by the computing device, a future operation of the computing device to comply with the new rule. 2. The method of claim 1 , wherein controlling the future operation of the computing device comprises determining whether to store the future image data. 3. The method of claim 1 , wherein controlling the future operation of the computing device comprises determining whether to automatically upload future generated image data to cloud storage. 4. The method of claim 1 , wherein identifying, by the computing device, one or more objects in the first scene comprises at least one of identifying a person using face detection, identifying a gesture performed by a person in the image, or detecting an action performed by a person in the image. 5. The method of claim 1 , further comprising generating, by the computing device, the image data and the audio data. 6. The method of claim 1 , wherein the computing device is a camera. 7. The method of claim 1 , wherein the transcription of the audio data is obtained using automated speech recognition. 8. The method of claim 1 , wherein the one or more objects in the first scene is identified using computer vision. 9. The computer-implemented method of claim 1 , wherein: the human speech utterance further describes the image capture behavior of the computing device in response to future instances of identification of the first object; and the method further comprises determining, by the computing device, the requested image capture behavior based at least in part on the transcription. 10. The computer-implemented method of claim 9 , wherein: the human speech utterance requests the computing device not capture imagery in response to future instances of identification of the first object in the future image data; and defining, by the computing device, the new rule comprises defining, by the computing device, the new rule that specifies that the computing device does not capture imagery in response to future instances of identification of the first object in the future image data. 11. The computer-implemented method of claim 1 , wherein: the human speech utterance self-references a speaker of the human speech utterance; and identifying, by the computing device based at least in part on the transcription and based at least in part on the image data, at least the first object that is referred to by the human speech utterance comprises identifying, by the computing device based at least in part on the image data, the speaker of the human speech utterance. 12. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining, by the one or more computers, (i) image data that describes a first scene and (ii) audio data; identifying one or more objects in the first scene based on the image data; obtaining a transcription of a human speech utterance described by the audio data, wherein the human speech utterance refers to at least a first object of the one or more objects included in the first scene; identifying, based at least in part on the transcription and based at least in part on the image data, at least the first object that is referred to by the human speech utterance; defining a new rule that specifies an image capture behavior of at least one of the one or more computers in response to future instances of identification of the first object in future image data that is different than the current image data; and controlling a future operation of the at least one of the one or more computers to comply with the new rule. 13. The system of claim 12 , wherein controlling a future operation of the at least one of the one or more computers comprises determining whether to store the future image data. 14. The system of claim 12 , wherein controlling a future operation of the at least one of the one or more computers comprises determining whether to automatically upload future generated image data to cloud storage. 15. The system of claim 12 , wherein identifying one or more objects in the first scene comprises at least one of identifying a person using face detection, identifying a gesture performed by a person in the first scene, or detecting an action performed by a person in the first scene. 16. The system of claim 12 , further comprising generating, by the one or more computers, the image data and the audio data. 17. The system of claim 12 , wherein the one or more computers comprise a camera. 18. The system of claim 12 , wherein the transcription of the audio data is obtained using automated speech recognition. 19. The system of claim 12 , wherein the one or more objects in the first scene is identified using computer vision. 20. A non-transitory, computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining (i) image data that describes a first scene and (ii) audio data; identifying one or more objects in the first scene based on the image data; obtaining a transcription of a human speech utterance described by the audio data, wherein the human speech utterance refers to at least a first object of the one or more objects included in the first scene; identifying, based at least in part on the transcription and based at least in part on the image data, at least the first object that is referred to by the human speech utterance; defining a new rule that specifies an image capture behavior of the one or more computers in response to future instances of identification of the first object in future image data that is different than the current image data; and controlling a future operation of the one or more computers to comply with the new rule.
where the recognised objects include parts of the human body · CPC title
Speech to text systems (G10L15/08 takes precedence) · CPC title
Remote control of cameras or camera parts, e.g. by remote control devices · CPC title
Execution procedure of a spoken command · CPC title
Procedures used during a speech recognition process, e.g. man-machine dialogue · CPC title
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