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» Machine Learning, Machine Vision, and the Brain
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ICCV
2011
IEEE
14 years 4 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
175
Voted
CVPR
2009
IEEE
16 years 11 months ago
Localized Content-Based Image Retrieval Through Evidence Region Identification
Over the past decade, multiple-instance learning (MIL) has been successfully utilized to model the localized content-based image retrieval (CBIR) problem, in which a bag corresp...
Wu-Jun Li (Hong Kong University of Science and Tec...
219
Voted
CVPR
2001
IEEE
16 years 6 months ago
Rapid Object Detection using a Boosted Cascade of Simple Features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
Paul A. Viola, Michael J. Jones
ECCV
2008
Springer
16 years 5 months ago
Online Tracking and Reacquisition Using Co-trained Generative and Discriminative Trackers
Visual tracking is a challenging problem, as an object may change its appearance due to viewpoint variations, illumination changes, and occlusion. Also, an object may leave the fie...
Gérard G. Medioni, Qian Yu, Thang Ba Dinh
ICPR
2010
IEEE
15 years 4 months ago
Spatiotemporal-Boosted DCT Features for Head and Face Gesture Analysis
Automatic analysis of head gestures and facial expressions is a challenging research area and it has significant applications in humancomputer interfaces. In this study, facial la...
Hatice Çinar Akakin, Bülent Sankur