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» A General Framework for Combining Visual Trackers - The
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CVPR
1998
IEEE
14 years 9 months ago
Joint Probabilistic Techniques for Tracking Multi-Part Objects
Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying ch...
Christopher Rasmussen, Gregory D. Hager
CVPR
2005
IEEE
14 years 9 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
IEAAIE
1998
Springer
13 years 11 months ago
A Combined Probabilistic Framework for Learning Gestures and Actions
Abstract. In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is...
Francisco Escolano, Miguel Cazorla, Domingo Gallar...
AVSS
2008
IEEE
14 years 2 months ago
Person Tracking with Audio-Visual Cues Using the Iterative Decoding Framework
Tracking humans in an indoor environment is an essential part of surveillance systems. Vision based and microphone array based trackers have been extensively researched in the pas...
Shankar T. Shivappa, Mohan M. Trivedi, Bhaskar D. ...
ICIP
2007
IEEE
14 years 9 months ago
Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods
We propose a multi-modal object tracking algorithm that combines appearance, motion and audio information in a particle filter. The proposed tracker fuses at the likelihood level ...
Matteo Bregonzio, Murtaza Taj, Andrea Cavallaro