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:
Nov. 07, 2017

Filed:

May. 07, 2015
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Feng Tang, Cupertino, CA (US);

Ang Li, Cupertino, CA (US);

Xiaojin Shi, Cupertino, CA (US);

Assignee:

Apple Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); H04N 13/02 (2006.01); G06K 9/46 (2006.01); G06F 3/01 (2006.01); G06F 3/03 (2006.01); G06F 3/042 (2006.01); G06T 7/246 (2017.01); G06T 7/254 (2017.01); H04N 13/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00355 (2013.01); G06F 3/017 (2013.01); G06F 3/0304 (2013.01); G06F 3/0425 (2013.01); G06K 9/4609 (2013.01); G06T 7/246 (2017.01); G06T 7/254 (2017.01); H04N 13/0207 (2013.01); H04N 13/0271 (2013.01); G06T 2200/04 (2013.01); G06T 2207/30196 (2013.01); H04N 2013/0085 (2013.01);
Abstract

In the field of Human-computer interaction (HCI), i.e., the study of the interfaces between people (i.e., users) and computers, understanding the intentions and desires of how the user wishes to interact with the computer is a very important problem. The ability to understand human gestures, and, in particular, hand gestures, as they relate to HCI, is a very important aspect in understanding the intentions and desires of the user in a wide variety of applications. In this disclosure, a novel system and method for three-dimensional hand tracking using depth sequences is described. Some of the major contributions of the hand tracking system described herein include: 1.) a robust hand detector that is invariant to scene background changes; 2.) a bi-directional tracking algorithm that prevents detected hands from always drifting closer to the front of the scene (i.e., forward along the z-axis of the scene); and 3.) various hand verification heuristics.


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