MACHINE LEARNING METHOD AND APPARATUS FOR DETECTION AND CONTINUOUS FEATURE COMPARISON
Methods, systems, and apparatuses, among other things, may perform persistent object tracking and reidentification through detection and continuous feature comparison. For example, video frames may be received (e.g., from a camera, an application, or a data storage device) and an object of interest may be detected at a first position in a video frame and the object of interest may be detected at a second position in another video frame. A track associated with the object of interest may be generated based on the detected first and second positions of the object of interest.
1 . A method comprising:
receiving a plurality of video frames;
detecting a first object of interest in a first video frame of the plurality of video frames;
detecting the first object of interest in a second video frame of the plurality of video frames; and
generating, based on a first position of the first object in the first video frame and a second position of the first object in the second video frame, a first track associated with the first object of interest.
2 . The method of claim 1 , further comprising:
extracting a first feature associated with the first object of interest from the first video frame;
extracting a second feature associated with a second object of interest from the second video frame; and
comparing the first feature and the second feature, wherein
detecting the first object of interest in the second video frame is based on the comparison.
3 . The method of claim 1 , further comprising:
identifying a change of viewpoint from the first video frame to the second video frame, wherein detecting the first object of interest in the second video frame is based on the change of viewpoint.
4 . The method of claim 1 further comprising:
comparing the first object of interest to a plurality of stored objects; and
identifying the first object of interest based on the comparison.
5 . The method of claim 1 , further comprising assigning an object identifier to the first object of interest, wherein the first track includes the assigned object identifier.
6 . The method of claim 1 , further comprising assigning a class identifier to the first object of interest, wherein the first track includes the assigned class identifier.
7 . The method of claim 1 , further comprising:
detecting the first object of interest in a third video frame of the plurality of video frames;
generating, based on the second position of the first object in the second video frame and a third position of the first object in the third video frame, a second track associated with the first object of interest;
comparing the first track and the second track; and
extending, based on the comparison, the first track to include the second track.
8 . The method of claim 7 , further comprising predicting a propagation of the first track, wherein the comparison of the first track and the second track is based on the predicted propagation.
9 . The method of claim 1 . further comprising:
comparing the first track with a plurality of stored tracks; and
extending, based on the comparison, a stored track of the plurality of stored tracks to include the first track.
10 . The method of claim 1 , further comprising transmitting the first track associated with the first object of interest to a downstream application.
11 . A system comprising:
one or more processors; and
memory including instructions that, when executed by the one or more processors, cause the system to:
display a video;
detect a first object of interest in a first video segment of the video;
detect the first object of interest in a second video segment of the video; and
generate, based on a first position of the first object in the first video segment and a second position of the first object in the second video segment, a first track associated with the first object of interest.
12 . The system of claim 11 , wherein the instructions are further configured to cause the system to:
extract a first feature associated with the first object of interest from the first segment;
extract a second feature associated with a second object of interest from the second video segment; and
compare the first feature and the second feature, wherein
detecting the first object of interest in the second video segment is based on the comparison.
13 . The system of claim 11 , wherein the instructions are further configured to cause the system to identify a change of viewpoint from the first video segment to the second video segment, wherein detecting the first object of interest in the second video segment is based on the change of viewpoint.
14 . The system of claim 11 , wherein the instructions are further configured to cause the system to:
compare the first object of interest to a plurality of stored objects; and
identify the first object of interest based on the comparison.
15 . The system of claim 11 , wherein the instructions are further configured to cause the system to assign an object identifier to the first object of interest, wherein the first track includes the assigned object identifier.
16 . The system of claim 11 , wherein the instructions are further configured to assign a class identifier to the first object of interest, wherein the first track includes the assigned class identifier.
17 . The system of claim 11 , wherein the instructions are further configured to cause the system to:
detect the first object of interest in a third video segment of the video;
generate, based on the second position of the first object in the second video frame and a third position of the first object in the third video frame, a second track associated with the first object of interest;
compare the first track and the second track; and
extend, based on the comparison, the first track to include the second track.
18 . The system of claim 17 , wherein the instructions are further configured to predict a propagation of the first track, wherein the comparison of the first track and the second track is based on the predicted propagation.
19 . The system of claim 11 , wherein the instructions are further configured to cause the system to:
compare the first track with a plurality of stored tracks; and
extend, based on the comparison, a stored track of the plurality of stored tracks to include the first track.
20 . A computer program product comprising:
a computer-readable storage medium; and
instructions stored on the computer-readable storage medium that, when executed by a processor, causes the processor to:
detect a first object of interest in a first video frame;
detect the first object of interest in a second video frame; and
generate, based on a first position of the first object in the first video frame and a second position of the first object in the second video frame, a first track associated with the first object of interest.