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» Bayesian Self-Calibration of a Moving Camera
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ECCV
2002
Springer
14 years 9 months ago
Audio-Video Sensor Fusion with Probabilistic Graphical Models
Abstract. We present a new approach to modeling and processing multimedia data. This approach is based on graphical models that combine audio and video variables. We demonstrate it...
Matthew J. Beal, Hagai Attias, Nebojsa Jojic
ECCV
2000
Springer
14 years 9 months ago
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
ICIP
2005
IEEE
14 years 9 months ago
Explicit contour model for vehicle tracking with automatic hypothesis validation
This paper addresses the problem of vehicle tracking under a single static, uncalibrated camera without any constraints on the scene or on the motion direction of vehicles. We int...
Boris Wai-Sing Yiu, Kwan-Yee Kenneth Wong, Francis...
ICCV
2011
IEEE
12 years 7 months ago
Manhattan Scene Understanding Using Monocular, Stereo, and 3D Features
This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through struct...
Alex Flint, David Murray, Ian Reid
AVSS
2006
IEEE
14 years 1 months ago
3D Human Motion Analysis in Monocular Video Techniques and Challenges
Extracting meaningful 3D human motion information from video sequences is of interest for applications like intelligent humancomputer interfaces, biometrics, video browsing and ind...
Cristian Sminchisescu