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:
Apr. 20, 2021

Filed:

Jul. 25, 2018
Applicant:

Ricoh Company, Ltd., Tokyo, JP;

Inventors:

Genki Watanabe, Tokyo, JP;

Hiroyoshi Sekiguchi, Kanagawa, JP;

Soichiro Yokota, Kanagawa, JP;

Seiya Amano, Kanagawa, JP;

Yuu Yamada, Kanagawa, JP;

Keito Sawada, Tokyo, JP;

Assignee:

RICOH COMPANY, LTD., Tokyo, JP;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 5/00 (2006.01); G06T 7/00 (2017.01); G06T 7/20 (2017.01); G06T 7/246 (2017.01); G06T 7/285 (2017.01); G06T 7/80 (2017.01); G06T 7/593 (2017.01); G06T 3/40 (2006.01); G08G 1/16 (2006.01); H04N 13/239 (2018.01); H04N 13/00 (2018.01);
U.S. Cl.
CPC ...
G06T 5/006 (2013.01); G06T 7/00 (2013.01); G06T 7/20 (2013.01); G06T 7/248 (2017.01); G06T 7/285 (2017.01); G06T 7/80 (2017.01); G08G 1/16 (2013.01); G08G 1/166 (2013.01); B60R 2300/105 (2013.01); B60R 2300/107 (2013.01); G06T 3/40 (2013.01); G06T 7/593 (2017.01); G06T 2207/10021 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20092 (2013.01); G06T 2207/30252 (2013.01); H04N 13/239 (2018.05); H04N 2013/0081 (2013.01);
Abstract

Disclosed is an image processing apparatus that includes one or more processors; and a memory storing instructions, which when executed by the one or more processors, cause the one or more processors to: generate distribution data indicating a frequency distribution of horizontal distance values of a range image based on the range image having pixel values according to distance of an object in a plurality of captured images; detect an object based on the distribution data with respect to a range image; predict a predicted position of the object in a current frame based on the distribution data with respect to range images of a plurality of previous frames; and integrate a plurality of objects detected by the detector based on the predicted position to track an integrated object in subsequent frames.


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