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» High-Level Feature Extraction Experiments for TRECVID 2007
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ICMCS
2007
IEEE
132views Multimedia» more  ICMCS 2007»
14 years 1 months ago
An SVM Framework for Genre-Independent Scene Change Detection
We present a novel genre-independent SVM framework for detecting scene changes in broadcast video. Our framework works on content from a diverse range of genres by allowing sets o...
Naveen Goela, Kevin W. Wilson, Feng Niu, Ajay Diva...
3DIM
2007
IEEE
14 years 1 months ago
Robust 2D-3D alignment based on geometrical consistency
This paper presents a new registration algorithm of a 2D image and a 3D geometrical model, which is robust for initial registration errors, for reconstructing a realistic 3D model...
Kenji Hara, Yuuki Kabashima, Yumi Iwashita, Ryo Ku...
ICDAR
2007
IEEE
13 years 11 months ago
Iterated Document Content Classification
We report an improved methodology for training classifiers for document image content extraction, that is, the location and segmentation of regions containing handwriting, machine...
Chang An, Henry S. Baird, Pingping Xiu
ICCV
2007
IEEE
14 years 9 months ago
People-LDA: Anchoring Topics to People using Face Recognition
Topic models have recently emerged as powerful tools for modeling topical trends in documents. Often the resulting topics are broad and generic, associating large groups of people...
Vidit Jain, Erik G. Learned-Miller, Andrew McCallu...
NIPS
2004
13 years 8 months ago
Two-Dimensional Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
Jieping Ye, Ravi Janardan, Qi Li