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MM
2005
ACM
250views Multimedia» more  MM 2005»
15 years 5 months ago
An object-based video coding framework for video sequences obtained from static cameras
This paper presents a novel object-based video coding framework for videos obtained from a static camera. As opposed to most existing methods, the proposed method does not require...
Asaad Hakeem, Khurram Shafique, Mubarak Shah
CVPR
2010
IEEE
15 years 7 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
DAGM
2006
Springer
15 years 3 months ago
On-Line, Incremental Learning of a Robust Active Shape Model
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
ICCV
2009
IEEE
2030views Computer Vision» more  ICCV 2009»
16 years 4 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 ...
ICIP
2006
IEEE
16 years 1 months ago
A Profile Hidden Markov Model Framework for Modeling and Analysis of Shape
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas