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CLOR
2006
14 years 1 months ago
Comparison of Generative and Discriminative Techniques for Object Detection and Classification
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the dis...
Ilkay Ulusoy, Christopher M. Bishop
VMV
2003
151views Visualization» more  VMV 2003»
13 years 11 months ago
Optimized Spatial Hashing for Collision Detection of Deformable Objects
We propose a new approach to collision and self– collision detection of dynamically deforming objects that consist of tetrahedrons. Tetrahedral meshes are commonly used to repre...
Matthias Teschner, Bruno Heidelberger, Matthias M&...
CVPR
2009
IEEE
15 years 5 months ago
An Empirical Study of Context in Object Detection
This paper presents an empirical evaluation of the role of context in a contemporary, challenging object detection task – the PASCAL VOC 2008. Previous experiments with context...
Alexei A. Efros, Derek Hoiem, James Hays, Martial ...
ICIP
2007
IEEE
14 years 12 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
WIAMIS
2009
IEEE
14 years 4 months ago
Towards fully un-supervised methods for generating object detection classifiers using social data
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...
Spiros Nikolopoulos, Elisavet Chatzilari, Eirini G...