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ICPR
2010
IEEE
13 years 7 months ago
High-Level Feature Extraction Using SIFT GMMs and Audio Models
—We propose a statistical framework for high-level feature extraction that uses SIFT Gaussian mixture models (GMMs) and audio models. SIFT features were extracted from all the im...
Nakamasa Inoue, Tatsuhiko Saito, Koichi Shinoda, S...
CVPR
2005
IEEE
14 years 9 months ago
Semi-Supervised Adapted HMMs for Unusual Event Detection
We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the applica...
Dong Zhang, Daniel Gatica-Perez, Samy Bengio, Iain...
AVSS
2007
IEEE
14 years 1 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen
PAMI
2008
189views more  PAMI 2008»
13 years 7 months ago
Detecting Objects of Variable Shape Structure With Hidden State Shape Models
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...

Publication
363views
12 years 6 months ago
Detecting and Discriminating Behavioural Anomalies
This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex tempor...
Chen Change Loy, Tao Xiang, Shaogang Gong