Online learning method for people detection and counting for retail stores
First Claim
Patent Images
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.
3 Assignments
0 Petitions
Accused Products
Abstract
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.
97 Citations
21 Claims
-
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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
-
-
11. A system for detecting people in a stream of images, the system comprising:
-
an output module implemented by a processor, the output module configured to output 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; andan update module implemented by the processor and configured to; identify 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 colors 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 update the object classifier using the training samples identified. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
-
-
21. A non-transitory computer readable medium having stored thereon a sequence of instructions which, when loaded and executed by a processor coupled to an apparatus, causes the apparatus to:
-
output 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;identify 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 update the object classifier using the training samples identified.
-
Specification