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.
Patent No.:
Date of Patent:
Jul. 02, 2019
Filed:
Jun. 27, 2016
Electronics and Telecommunications Research Institute, Daejeon, KR;
Sogang University Research Foundation, Seoul, KR;
Diquest Inc., Seoul, KR;
Soongsil University Research Consortium Techno-park, Seoul, KR;
Pukyong National University Industry-university Cooperation Foundation, Busan, KR;
Kyeong Deok Moon, Daejeon, KR;
Jong Ho Nang, Seoul, KR;
Yun Kyung Park, Daejeon, KR;
Kyung Sun Kim, Hwaseong-si, KR;
Chae Kyu Kim, Daejeon, KR;
Ki Ryong Kwon, Busan, KR;
Kyoung Ju Noh, Daejeon, KR;
Young Tack Park, Seoul, KR;
Kwang Il Lee, Daejeon, KR;
Electronics and Telecommunications Research Institute, Daejeon, KR;
SOGANG UNIVERSITY RESEARCH FOUNDATION, Seoul, KR;
DIQUEST INC., Seoul, KR;
Soongsil University Research Consortium techno-PARK, Seoul, KR;
Pukyong National University Industry-University Cooperation Foundation, Busan, KR;
Abstract
Provided are a system and method for automatically recreating personal media through fusion of multimodal features. The system includes a multimodal fusion analyzer configured to analyze semantics of personal media having various forms based on a plurality of modalities and divide the personal media into media fragments which are the smallest units having semantics, a semantic-based intelligent retriever configured to store and retrieve the divided media fragments by considering the semantics, a personal media recommender configured to learn and analyze a profile of a user through modeling the user, and select and recommend a plurality of media fragments wanted by the user among the media fragments retrieved by the semantic-based intelligent retriever, and a personal media creator configured to create new personal media using the plurality of media fragments recommended by the personal media recommender according to a scenario input by the user.