The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 25, 2015
Filed:
Apr. 20, 2012
Vinay Damodar Shet, Princeton, NJ (US);
Dorin Comaniciu, Princeton Junction, NJ (US);
Sushil Mittal, Highland Park, NJ (US);
Peter Meer, East Brunswick, NJ (US);
Cheng-hao Kuo, Plainsboro, NJ (US);
Vinay Damodar Shet, Princeton, NJ (US);
Dorin Comaniciu, Princeton Junction, NJ (US);
Sushil Mittal, Highland Park, NJ (US);
Peter Meer, East Brunswick, NJ (US);
Cheng-Hao Kuo, Plainsboro, NJ (US);
Siemens Aktiengesellschaft, Munich, DE;
Rutgers University, New Brunswick, NJ (US);
Abstract
A method for tracking pedestrians in a video sequence, where each image frame of the video sequence corresponds to a time step, includes using marginal space learning to sample a prior probability distribution p(x|Z) of multi-person identity assignments given a set of feature measurements from all previous image frames, using marginal space learning to estimate an observation likelihood distribution p(z|x) of the set of features given a set of multi-person identity assignments sampled from the prior probability distribution, calculating a posterior probability distribution p(x|Z) from the observation likelihood distribution p(z|x) and the prior probability distribution p(x|Z), and using marginal space learning to estimate the prior probability distribution p(x|Z) for a next image frame given the posterior probability distribution p(x|Z) and a probability p(x|x), where the posterior probability distribution of multi-person identity assignments corresponds to a set of pedestrian detection hypotheses for the video sequence.