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:
Sep. 30, 2014

Filed:

Sep. 04, 2009
Applicants:

Santanu Chaudhury, New Delhi, IN;

Mona Mathur, Delhi, IN;

Aditya Khandelia, Madhya Pradesh, IN;

Subarna Tripathi, Karnataka, IN;

Brejesh Lall, New Delhi, IN;

Sumantra Dutta Roy, New Delhi, IN;

Saurabh Gorecha, Chennai, IN;

Inventors:

Santanu Chaudhury, New Delhi, IN;

Mona Mathur, Delhi, IN;

Aditya Khandelia, Madhya Pradesh, IN;

Subarna Tripathi, Karnataka, IN;

Brejesh Lall, New Delhi, IN;

Sumantra Dutta Roy, New Delhi, IN;

Saurabh Gorecha, Chennai, IN;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04B 1/66 (2006.01); H04N 7/12 (2006.01); H04N 11/02 (2006.01); H04N 11/04 (2006.01); H04N 19/139 (2014.01); H04N 19/14 (2014.01); H04N 19/20 (2014.01); H04N 19/132 (2014.01); H04N 19/17 (2014.01); H04N 19/12 (2014.01); H04N 19/61 (2014.01); H04N 19/159 (2014.01); G06T 7/20 (2006.01); H04N 19/436 (2014.01);
U.S. Cl.
CPC ...
H04N 19/00521 (2013.01); H04N 19/00151 (2013.01); H04N 19/00157 (2013.01); H04N 19/00387 (2013.01); H04N 19/00127 (2013.01); G06T 2207/10016 (2013.01); H04N 19/0026 (2013.01); H04N 19/00078 (2013.01); H04N 19/00781 (2013.01); H04N 19/00218 (2013.01); G06T 7/2006 (2013.01);
Abstract

A video compression framework based on parametric object and background compression is proposed. At the encoder, an embodiment detects objects and segments frames into regions corresponding to the foreground object and the background. The object and the background are individually encoded using separate parametric coding techniques. While the object is encoded using the projection coefficients to the orthonormal basis of the learnt subspace (used for appearance based object tracking), the background is characterized using an auto-regressive (AR) process model. An advantage of the proposed schemes is that the decoder structure allows for simultaneous reconstruction of object and background, thus making it amenable to the new multi-thread/multi-processor architectures.


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