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» Probabilistic Object Tracking Using Multiple Features
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CVPR
2006
IEEE
14 years 11 months ago
Robust Fragments-based Tracking using the Integral Histogram
We present a novel algorithm (which we call "FragTrack") for tracking an object in a video sequence. The template object is represented by multiple image fragments or pa...
Amit Adam, Ehud Rivlin, Ilan Shimshoni
ECCV
1998
Springer
14 years 11 months ago
A Two-Stage Probabilistic Approach for Object Recognition
Assume that some objects are present in an image but can be seen only partially and are overlapping each other. To recognize the objects, we have to rstly separate the objects from...
Stan Z. Li, Joachim Hornegger
CLOR
2006
14 years 23 days ago
Sequential Learning of Layered Models from Video
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
Michalis K. Titsias, Christopher K. I. Williams
VIS
2007
IEEE
113views Visualization» more  VIS 2007»
14 years 10 months ago
Texture-based Feature Tracking for Effective Time-varying Data Visualization
Analyzing, visualizing, and illustrating changes within time-varying volumetric data is challenging due to the dynamic changes occurring between timesteps. The changes and variatio...
Jesus Caban, Alark Joshi, Penny Rheingans
ECCV
2004
Springer
14 years 11 months ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona