Logical sensor generation in a behavioral recognition system
View Patent ↗Techniques are disclosed for generating logical sensors for an image driver. The image driver monitors values corresponding to at least a first feature in one or more regions of a first image in a stream of images received by a first sensor. The image driver identifies at least a first correlation between at least a first and second value of the monitored values. The image driver generates a logical sensor based on the identified correlations. The logical sensor samples one or more features corresponding to the identified correlation from a second image in the stream of images.
1. A computer-implemented method comprising:
monitoring values corresponding to at least a first feature in at least two regions of a first image in a stream of images received by a first sensor;
identifying at least a first correlation between at least a first value and a second value of the monitored values; and
generating a logical sensor based on the at least first correlation, wherein the logical sensor samples one or more features corresponding to the at least first correlation from a second image in the stream of images.
2. The method of claim 1 , wherein the first feature is derived based on pixel values in the image.
3. The method of claim 1 , wherein the logical sensor generates a plurality of feature vectors from the second image.
4. The method of claim 3 , further comprising:
generating a sample vector from the plurality of feature vectors.
5. The method of claim 4 , further comprising:
sending the sample vector to a sample memory for retrieval by a machine learning engine that evaluates the sample vector.
6. The method of claim 1 , wherein the first sensor captures the stream of images, and wherein the first sensor is a camera.
7. The method of claim 6 , wherein the camera is an infrared camera or a visible camera.
8. A non-transitory computer-readable storage medium having instructions, which, when executed on a processor, performs an operation, comprising:
monitoring values corresponding to at least a first feature in at least two regions of a first image in a stream of images received by a first sensor;
identifying at least a first correlation between at least a first value and a second value of the monitored values; and
generating a logical sensor based on the at least first correlation, wherein the logical sensor samples one or more features corresponding to the at least first correlation from a second image in the stream of images.
9. The computer-readable storage medium of claim 8 , wherein the first feature is derived based on pixel values in the image.
10. The computer-readable storage medium of claim 8 , wherein the logical sensor generates a plurality of feature vectors from the second image.
11. The computer-readable storage medium of claim 10 , wherein the operation further comprises:
generating a sample vector from the plurality of feature vectors.
12. The computer-readable storage medium of claim 11 , wherein the operation further comprises:
sending the sample vector to a sample memory for retrieval by a machine learning engine that evaluates the sample vector.
13. The computer-readable storage medium of claim 8 , wherein the first sensor captures the stream of images, and wherein the first sensor is a camera.
14. The computer-readable storage medium of claim 13 , wherein the camera is an infrared camera or a visible camera.
15. A system, comprising:
a processor; and
a memory storing code, which, when executed on the processor, performs an operation, comprising:
monitoring values corresponding to at least a first feature in at least two regions of a first image in a stream of images received by a first sensor,
identifying at least a first correlation between at least a first value and a second value of the monitored values, and
generating a logical sensor based on the at least first correlation, wherein the logical sensor samples one or more features corresponding to the at least first correlation from a second image in the stream of images.
16. The system of claim 15 , wherein the first feature is derived based on pixel values in the image.
17. The system of claim 15 , wherein the logical sensor generates a plurality of feature vectors from the second image.
18. The system of claim 17 , wherein the operation further comprises:
generating a sample vector from the plurality of feature vectors.
19. The system of claim 18 , wherein the operation further comprises:
sending the sample vector to a sample memory for retrieval by a machine learning engine that evaluates the sample vector.
20. The system of claim 15 , wherein the first sensor captures the stream of images, and wherein the first sensor is a camera.