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GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
14 years 28 days ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai
CVPR
2009
IEEE
15 years 2 months ago
Learning color and locality cues for moving object detection and segmentation
This paper presents an algorithm for automatically detecting and segmenting a moving object from a monocular video. Detecting and segmenting a moving object from a video with limit...
Feng Liu (University of Wisconsin-Madison), Michae...
DICTA
2009
13 years 8 months ago
Improved Simultaneous Computation of Motion Detection and Optical Flow for Object Tracking
Abstract--Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segmen...
Simon Denman, Clinton Fookes, Sridha Sridharan
PR
2011
12 years 10 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 tempo...
Chen Change Loy, Tao Xiang, Shaogang Gong
TCSV
2008
174views more  TCSV 2008»
13 years 7 months ago
A Survey of Vision-Based Trajectory Learning and Analysis for Surveillance
Abstract--This paper presents a survey of trajectory-based activity analysis for visual surveillance. It describes techniques that use trajectory data to define a general set of ac...
Brendan Tran Morris, Mohan M. Trivedi