Camera time-based motion trails and motion heat-maps for periodic captured images
Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for generating a long exposure composite image (LECI) frame, wherein the LECI frame provides a summary of activity in a monitored environment over a duration of time. An embodiment captures, using an image-capturing device, a sequence of image frames over the duration of time using an optical sensor of the image-capturing device. The embodiment then generates the LECI frame, using an embedded low-power processor coupled to the optical sensor and dedicated to generating LECI frames, by combining the sequence of image frames. The embodiment then transmits the LECI frame to a network device using a transceiver coupled to the low-power processor.
1. A computer-implemented method for generating a long exposure composite image (LECI) frame, wherein the LECI frame provides a summary of activity in a monitored environment over a duration of time, comprising:
capturing, by at least one computer processor of an image-capturing device, a sequence of image frames over the duration of time using an optical sensor of the image-capturing device;
generating, using an embedded low-power processor coupled to the optical sensor and dedicated to generating LECI frames, the LECI frame by combining the sequence of image frames; and
transmitting, using a transceiver coupled to the embedded low-power processor, the LECI frame to a network device.
2. The computer-implemented method of claim 1 , wherein the sequence of image frames comprises a first set of image frames and a second set of image frames, wherein the first set of image frames is associated with a first time period within the duration of time and the second set of image frames is associated with a second time period within the duration of time, wherein the first time period is more recent than the second time period, and wherein generating the LECI frame comprises:
performing a weighted averaging of the sequence of image frames by:
assigning a first set of weights to the first set of image frames of the sequence of image frames; and
assigning a second set of weights to the second set of image frames, wherein each of the first set of weights is greater than all of the second set of weights.
3. The computer-implemented method of claim 1 , wherein generating the LECI frame comprises:
combining the sequence of image frames by computing a pixel-wise weighted average of pixel values across the sequence of image frames.
4. The computer-implemented method of claim 1 , wherein generating the LECI frame comprises:
identifying a moving object in one or more image frames of the sequence of image frames; and
performing the weighted averaging by assigning higher weights to pixels corresponding to the moving object in the one or more image frames.
5. The computer-implemented method of claim 1 , wherein generating the LECI frame comprises:
identifying relative displacement of one or more pixels between a set of image frames of the sequence of image frames to generate one or more direction vectors indicating direction of motion of an object in the sequence of image frames.
6. The computer-implemented method of claim 1 , wherein capturing the sequence of image frames comprises:
capturing the sequence of image frames at a capture-rate that is proportional to a measure of activity in the monitored environment.
7. The computer-implemented method of claim 1 , wherein the duration of time is inversely proportional to a measure of activity in the monitored environment.
8. The computer-implemented method of claim 1 , wherein the image-capturing device is a battery-operated camera.
9. A system for generating a long exposure composite image (LECI) frame, wherein the LECI frame provides a summary of activity in a monitored environment over a duration of time, comprising:
one or more memories; and
at least one processor coupled to at least one of one or more memories of an image-capturing device and configured to perform operations comprising:
capturing a sequence of image frames over the duration of time using an optical sensor of the image-capturing device;
generating, using an embedded low-power processor coupled to the optical sensor and dedicated to generating LECI frames, the LECI frame by combining the sequence of image frames; and
transmitting, using a transceiver coupled to the embedded low-power processor, the LECI frame to a network device.
10. The system of claim 9 , wherein the sequence of image frames comprises a first set of image frames and a second set of image frames, wherein the first set of image frames is associated with a first time period within the duration of time and the second set of image frames is associated with a second time period within the duration of time, wherein the first time period is more recent than the second time period, and wherein generating the LECI frame comprises:
performing a weighted averaging of the sequence of image frames by:
assigning a first set of weights to the first set of image frames of the sequence of image frames; and
assigning a second set of weights to the second set of image frames, wherein each of the first set of weights is greater than all of the second set of weights.
11. The system of claim 9 , wherein generating the LECI frame comprises:
combining the sequence of image frames by computing a pixel-wise weighted average of pixel values across the sequence of image frames.
12. The system of claim 9 , wherein generating the LECI frame comprises:
identifying a moving object in one or more image frames of the sequence of image frames; and
performing a weighted averaging by assigning higher weights to pixels corresponding to the moving object in the one or more image frames.
13. The system of claim 9 , wherein generating the LECI frame comprises:
identifying relative displacement of one or more pixels between a set of image frames of the sequence of image frames to generate one or more direction vectors indicating direction of motion of an object in the sequence of image frames.
14. The system of claim 9 , wherein capturing the sequence of image frames comprises:
capturing the sequence of image frames at a capture-rate that is proportional to a measure of activity in the monitored environment.
15. The system of claim 9 , wherein the duration of time is inversely proportional to a measure of activity in the monitored environment.
16. A non-transitory computer-readable medium having instructions stored thereon that, when executed by at least one computing device, cause the at least one computing device to perform operations for generating a long exposure composite image (LECI) frame, wherein the LECI frame provides a summary of activity in a monitored environment over a duration of time, the operations comprising:
capturing, by at least one computer processor of an image-capturing device, a sequence of image frames over the duration of time using an optical sensor of the image-capturing device;
generating, using an embedded low-power processor coupled to the optical sensor and dedicated to generating LECI frames, the LECI frame by combining the sequence of image frames; and
transmitting, using a transceiver coupled to the embedded low-power processor, the LECI frame to a network device.
17. The non-transitory computer-readable medium of claim 16 , wherein the sequence of image frames comprises a first set of image frames and a second set of image frames, wherein the first set of image frames is associated with a first time period within the duration of time and the second set of image frames is associated with a second time period within the duration of time, wherein the first time period is more recent than the second time period, and wherein generating the LECI frame comprises:
performing a weighted averaging of the sequence of image frames by:
assigning a first set of weights to the first set of image frames of the sequence of image frames; and
assigning a second set of weights to the second set of image frames, wherein each of the first set of weights is greater than all of the second set of weights.
18. The non-transitory computer-readable medium of claim 16 , wherein generating the LECI frame comprises:
combining the sequence of image frames by computing a pixel-wise weighted average of pixel values across the sequence of image frames.
19. The non-transitory computer-readable medium of claim 16 , wherein generating the LECI frame comprises:
identifying a moving object in one or more image frames of the sequence of image frames; and
performing the weighted averaging by assigning higher weights to pixels corresponding to the moving object in the one or more image frames.
20. The non-transitory computer-readable medium of claim 16 , wherein capturing the sequence of image frames comprises:
capturing the sequence of image frames at a capture-rate that is proportional to a measure of activity in the monitored environment.