Fudan University at TRECVID 2008
نویسندگان
چکیده
FD IMI LK: This run is only based on the text from the English ASR/MT output provided by NIST and on the text of the topics. FD IMI ZYB: This run is based on the text search and the visual expand from the text search results. FD IMI HXS: This run is based on the concept mapping method. FD IMI ZJ: This run is based on the fusion of concept mapping and visual search. FD IMI ZW: This run is based on average fusion method. FD IMI SZC: This run is only based on multi-model fusion method.
منابع مشابه
Fudan University at TRECVID 2010 : Semantic Indexing
In this notebook paper we describe our participation in the NIST TRECVID 2010 evaluation. We took part in semantic indexing task of benchmark this year. For semantic indexing, we submitted 3 automatic runs using only IACC training data: Fudan.TV10.3: this run is based on visual features of keyframes. Fudan.TV10.2: this run is based on visual features of keyframes and object detection. Fudan.TV1...
متن کاملSymmetry based Structure Entropy of Complex Networks
Department of Computing and Information Technology, Fudan University, ShangHai 200433, PR China Business school, University of Shanghai for Science and Technology, Shanghai 200433, PR China Theoretical Systems Biology Lab , School of Life Science, Fudan University, Shanghai 200093, PR China and Human Genetics Center, University of Texas Health Science Center at Houston, Houston TX 77225, USA (D...
متن کاملBilkent University Multimedia Database Group at TRECVID 2008
Bilkent University Multimedia Database Group (BILMDG) participated in two tasks at TRECVID 2008: content-based copy detection (CBCD) and high-level feature extraction (FE). Mostly MPEG-7 [1] visual features, which are also used as low-level features in our MPEG-7 compliant video database management system, are extracted for these tasks. This paper discusses our approaches in each task.
متن کاملTRECVID-08 Participation at Bama and UNC-Chapel Hill
Researchers from the University of Alabama and the University of North Carolina at Chapel Hill collaborated on this study for TRECVID-08. This study focused on the search task of TRECVID-08, and the experiments included two full search runs, one interactive and one manual. Both search runs, M_C_2_ViewFinderALNC_2 and I_C_1_ViewFinderALNC_1, had similar designs. Each was conducted using the View...
متن کاملFudan University at TRECVID 2009: High-Level Feature Extraction and Copy Detection
For high-level feature extraction, we submitted 4 automatic runs: Fudan.Global: this run is based on global features of keyframes. Fudan.Local: this run is based on local features of keyframes. Fudan.Rerank: this run is based on local features and spatial information of keyframes. Fudan.Fusion: this run is based on the fusion of global and local features of keyframes. Focus of our system was on...
متن کامل