Incremental learning framework for object detection in videos

A non-transitory computer-readable storage medium having instructions, which, when executed on a processor, perform an operation comprising:

• identifying, based on an object detection model, one or more objects in a first sequence of video frames of a plurality of sequences of video frames, wherein the object detection model provides an object space including a plurality of object classes, wherein each object is classified as being an instance of one of the object classes, and wherein each object class includes one or more prototypes representing an instance of an object associated with the object class;
• and
• for each identified object:
• tracking the object across at least one of the frames,
• generating a measure of confidence for the object based on the tracking, wherein the measure of confidence indicates a degree that the object does not correspond to any of the one or more prototypes currently associated with the object class, and
• upon determining that the measure of confidence exceeds a threshold, adding a prototype representative of the instance to the object detection model.

A system, comprising:

• a processor;
• and
• a memory storing program code, which, when executed on the processor, performs an operation comprising:
• identifying, based on an object detection model, one or more objects in a first sequence of video frames of a plurality of sequences of video frames, wherein the object detection model provides an object space including a plurality of object classes, wherein each object is classified as being an instance of one of the object classes, and wherein each object class includes one or more prototypes representing an instance of an object associated with the object class, and
• for each identified object:
• tracking the object across at least one of the frames,
• generating a measure of confidence for the object based on the tracking, wherein the measure of confidence indicates a degree that the object does not correspond to any of the one or more prototypes currently associated with the object class, and
• upon determining that the measure of confidence exceeds a threshold, adding a prototype representative of the instance to the object detection model.