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.

Date of Patent:
Dec. 08, 2015

Filed:

May. 16, 2014
Applicant:

Tata Consultancy Services Limited, Mumbai, Maharashtra, IN;

Inventors:

Kingshuk Chakravarty, West Bengal, IN;

Aniruddha Sinha, West Bengal, IN;

Diptesh Das, West Bengal, IN;

Rohan Banerjee, West Bengal, IN;

Amit Konar, Kolkata, IN;

Sudeepto Dutta, Dist. Darjeeling, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/44 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00348 (2013.01); G06K 9/44 (2013.01); G06K 9/627 (2013.01);
Abstract

Method(s) and system(s) for identification of an unknown person are disclosed. The method includes receiving skeleton data comprises data of multiple skeleton joints of the unknown person from skeleton recording devices. The method further includes extracting G gait feature vectors from the skeleton data. Further, the method includes classifying each gait feature vector into one of N classes based on a training dataset for N known persons and computing a classification score for each class. The method also includes clustering the training dataset into M clusters based on M predefined characteristic attributes of the known persons, tagging each gait feature vector with one of the M clusters based on a distance between a respective gait feature vector and cluster centers of M clusters, and determining a clustering score for each M cluster. The method further includes identifying the unknown person based on clustering scores and classification scores.


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