Results 1 - 10 of 1,406

Kernel-Based Object Tracking

by Dorin Comaniciu, Visvanathan Ramesh, Peter Meer , 2003
"... A new approach toward target representation and localization, the central component in visual tracking of non-rigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity fu ..."
Abstract - Cited by 900 (4 self) - Add to MetaCart
A new approach toward target representation and localization, the central component in visual tracking of non-rigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity

A survey on visual surveillance of object motion and behaviors

by Weiming Hu, Tieniu Tan, Liang Wang, Steve Maybank - IEEE Transactions on Systems, Man and Cybernetics , 2004
"... Abstract—Visual surveillance in dynamic scenes, especially for humans and vehicles, is currently one of the most active research topics in computer vision. It has a wide spectrum of promising applications, including access control in special areas, human identification at a distance, crowd flux stat ..."
Abstract - Cited by 439 (6 self) - Add to MetaCart
—Behavior understanding and description, fusion of data from multiple cameras, motion detection, personal identification, tracking, visual surveillance.

Data fusion for visual tracking with particles

by Patrick Pérez, Jaco Vermaak, Andrew Blake - Proc. IEEE , 2004
"... Abstract—The effectiveness of probabilistic tracking of objects in image sequences has been revolutionized by the development of particle filtering. Whereas Kalman filters are restricted to Gaussian distributions, particle filters can propagate more general distributions, albeit only approximately. ..."
Abstract - Cited by 166 (2 self) - Add to MetaCart
. Although this fact has been acknowledged before, it has not been fully exploited within a visual tracking context. Here we introduce generic importance sampling mechanisms for data fusion and discuss them for fusing color with either stereo sound, for tele-conferencing, or with motion, for surveillance

Fusion with Diffusion for Robust Visual Tracking

by Yu Zhou, Xiang Bai, Wenyu Liu, Longin Jan Latecki
"... A weighted graph is used as an underlying structure of many algorithms like semisupervised learning and spectral clustering. If the edge weights are determined by a single similarity measure, then it hard if not impossible to capture all relevant aspects of similarity when using a single similarity ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
. Moreover, it is not necessary to explicitly construct the TPG in our framework. Finally all diffused pairs of similarity measures are combined as a weighted sum. We demonstrate the advantages of the proposed approach on the task of visual tracking, where different aspects of the appearance similarity

Tracking Loose-limbed People

by Leonid Sigal, Sidharth Bhatia, Stefan Roth, Michael J. Black, Michael Isard , 2004
"... We pose the problem of 3D human tracking as one of inference in a graphical model. Unlike traditional kinematic tree representations, our model of the body is a collection of loosely-connected limbs. Conditional probabilities relating the 3D pose of connected limbs are learned from motioncaptured tr ..."
Abstract - Cited by 191 (7 self) - Add to MetaCart
We pose the problem of 3D human tracking as one of inference in a graphical model. Unlike traditional kinematic tree representations, our model of the body is a collection of loosely-connected limbs. Conditional probabilities relating the 3D pose of connected limbs are learned from motioncaptured

Filters, Random Fields and Maximum Entropy . . .

by Song Chun Zhu, Yingnian Wu, David Mumford - INTERNATIONAL JOURNAL OF COMPUTER VISION , 1998
"... This article presents a statistical theory for texture modeling. This theory combines filtering theory and Markov random field modeling through the maximum entropy principle, and interprets and clarifies many previous concepts and methods for texture analysis and synthesis from a unified point of vi ..."
Abstract - Cited by 233 (16 self) - Add to MetaCart
sampler is adopted to synthesize texture images by drawing typical samples from p(I), thus the model is verified by seeing whether the synthesized texture images have similar visual appearances

Efficient Visual Tracking by Probabilistic Fusion of Multiple Cues

by unknown authors
"... It has been shown that integrating multiple cues will increase the reliability and robustness of a vision system in situations that no single cue is reliable. In this paper, we propose a method by fusing multiple cues (i.e., the color cue and the edge cue). In contrast to previous work, we propose a ..."
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a novel shape similarity measure which includes the spatial distribution of, the number of, and the gradient intensity of the edge points. We integrate this shape similarity measure with our recently proposed SMOG-based color similarity measure in the framework of particle filter (PF). Experimental

Probabilistic Tracking in a Metric Space

by Kentaro Toyama, Andrew Blake - in ICCV , 2001
"... A new, exemplar-based, probabilistic paradigm for visual tracking is presented. Probabilistic mechanisms are attractive because they handle fusion of information, especially temporal fusion, in a principled manner. Exemplars are selected representatives of raw training data, used here to represent p ..."
Abstract - Cited by 152 (3 self) - Add to MetaCart
A new, exemplar-based, probabilistic paradigm for visual tracking is presented. Probabilistic mechanisms are attractive because they handle fusion of information, especially temporal fusion, in a principled manner. Exemplars are selected representatives of raw training data, used here to represent

Tracking known three-dimensional objects

by Donald B. Gennery - In Proceedings of AAAI-82 , 1982
"... A method of visually tracking a known three-dimensional object is described. Predicted object position and orientation extrapolated from previous tracking data are used to find known features in one or more pictures. The measured image positions of the features are used to adjust the estimates of ob ..."
Abstract - Cited by 149 (1 self) - Add to MetaCart
A method of visually tracking a known three-dimensional object is described. Predicted object position and orientation extrapolated from previous tracking data are used to find known features in one or more pictures. The measured image positions of the features are used to adjust the estimates

Tightly Integrated Sensor Fusion for Robust Visual Tracking

by Georg Klein, Tom Drummond - In Proc. British Machine Vision Conference (BMVC’02 , 2002
"... This paper presents novel methods for increasing the robustness of visual tracking systems by incorporating information from inertial sensors. We show that more can be achieved than simply combining the sensor data within a statistical filter. In particular we show how, in addition to using inertial ..."
Abstract - Cited by 35 (7 self) - Add to MetaCart
This paper presents novel methods for increasing the robustness of visual tracking systems by incorporating information from inertial sensors. We show that more can be achieved than simply combining the sensor data within a statistical filter. In particular we show how, in addition to using
Results 1 - 10 of 1,406