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:
May. 27, 2014

Filed:

Jan. 12, 2011
Applicants:

Yuan Liu, Beijing, CN;

Tao LI, Beijing, CN;

Yinghui Xu, Kanagawa, JP;

Yi Chen, Beijing, CN;

Lei Zhang, Beijing, CN;

Inventors:

Yuan Liu, Beijing, CN;

Tao Li, Beijing, CN;

Yinghui Xu, Kanagawa, JP;

Yi Chen, Beijing, CN;

Lei Zhang, Beijing, CN;

Assignee:

Ricoh Company, Ltd., Tokyo, JP;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/60 (2006.01); G06K 9/62 (2006.01); G06K 9/46 (2006.01); G06K 9/66 (2006.01); G06F 17/00 (2006.01);
U.S. Cl.
CPC ...
Abstract

Disclosed are a method and a system for adding annotations into an input medium file. The method comprises a step of creating annotation detection models based on training samples formed by existing media files having annotations; a step of extracting coexistence coefficients of any two annotations based on appearance frequencies of the annotations in the training samples; a step of inputting the input medium file; a step of extracting sense-of-vision features from the input medium file; a step of obtaining initial annotations of the input medium file; a step of acquiring candidate annotations based on the initial annotations and the coexistence coefficients of the annotations in the training samples; and a step of selecting a final annotation set from the candidate annotations based on the sense-of-vision features of the input medium file and the coexistence coefficients by using the annotation detection models.


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