Training an object detector using raw and unlabeled videos and extracted speech

A computer-implemented method, comprising:

• receiving, via a processor, raw and unlabeled videos;
• extracting, via the processor, speech from the raw and unlabeled videos;
• extracting, via the processor, positive frames and negative frames from the raw and unlabeled videos based on the extracted speech for each object to be detected;
• extracting, via the processor, region proposals from the positive frames and negative frames;
• extracting, via the processor, features based on the extracted region proposals;
• clustering, via the processor, the region proposals and assign a potential score to each cluster;
• and
• training, via the processor, a binary object detector to detect objects based on positive samples selected based on potential score.

A computer program product for training object detectors, the computer program product comprising a computer-readable storage medium having program code embodied therewith, the program code executable by a processor to cause the processor to:

• receive raw and unlabeled videos;
• extract speech from the raw and unlabeled videos;
• extract positive frames and negative frames from the raw and unlabeled videos based on the extracted speech for each object to be detected;
• extract region proposals from the positive frames and negative frames;
• extract features based on the extracted region proposals;
• cluster the region proposals and assign a potential score to each cluster;
• and
• train a binary object detector to detect objects based on positive samples randomly selected using the potential score.