Online learning method for people detection and counting for retail stores

摘要

People detection can provide valuable metrics that can be used by businesses, such as retail stores. Such information can be used to influence any number of business decisions such a employment hiring and product orders. The business value of this data hinges upon its accuracy. Thus, a method according to the principles of the current invention outputs metrics regarding people in a video frame within a stream of video frames through use of an object classifier configured to detect people. The method further comprises automatically updating the object classifier using data in at least a subset of the video frames in the stream of video frames.

主权项

1. A method of detecting people in a stream of images, the method comprising:
outputting metrics regarding people in a first subset of video frames within a stream of video frames through use of an object classifier configured to detect people as a function of image gradients calculated for edge information of objects, histogram of oriented gradient (HOG) features extracted from the image gradients calculated for the edge information, and automatically tunable coefficients; the edge information including edge data of a head-shoulder area of the people; identifying training samples by detecting a head-shoulder area in a second subset of video frames within the stream of video frames using at least one of (i) template matching and (ii) motion blobs and color blobs extracted from motion pixels and skin color pixels, the second subset of video frames including fewer frames than the first subset of video frames; and automatically updating the object classifier using the training samples identified.