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ICCV
2009
IEEE
2030views Computer Vision» more  ICCV 2009»
16 years 11 months ago
Robust Tracking-by-Detection using a Detector Confidence Particle Filter
We propose a novel approach for multi-person trackingby- detection in a particle filtering framework. In addition to final high-confidence detections, our algorithm uses the con...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
ICCV
2009
IEEE
16 years 10 months ago
Sparsity Induced Similarity Measure for Label Propagation
Graph-based semi-supervised learning has gained considerable interests in the past several years thanks to its effectiveness in combining labeled and unlabeled data through labe...
Hong Cheng, Zicheng Liu, Jie Yang
CVPR
2007
IEEE
16 years 8 months ago
Learning Features for Tracking
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
Michael Grabner, Helmut Grabner, Horst Bischof
ICIP
2008
IEEE
16 years 8 months ago
Estimation and representation of accumulated motion characteristics for semantic event detection
In this paper, a motion-based approach for detecting high-level semantic events in video sequences is presented. Its main characteristic is its generic nature, i.e. it can be dire...
Georgios Th. Papadopoulos, Vasileios Mezaris, Ioan...
PLPV
2010
ACM
16 years 3 months ago
Resource typing in Guru
This paper presents a resource typing framework for the Guru d-programming language, in which abstractions for various kinds of program resources can be defined. Implemented exam...
Aaron Stump, Evan Austin