Visual tracking of known three-dimensional objects
International Journal of Computer Vision
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Convergence of a branching particle method to the solution of the Zakai equation
SIAM Journal on Applied Mathematics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optical Flow Constraints on Deformable Models with Applications to Face Tracking
International Journal of Computer Vision
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filtering Image Records Using Wavelets and the Zakai Equation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Object Localization by Bayesian Correlation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Tracking through Singularities and Discontinuities by Random Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Combining View-Based and Model-Based Tracking of Articulated Human Movements
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamical Statistical Shape Priors for Level Set-Based Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking People by Learning Their Appearance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proposal maps driven MCMC for estimating human body pose in static images
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Capture and representation of human walking in live video sequences
IEEE Transactions on Multimedia
Optimal edge-based shape detection
IEEE Transactions on Image Processing
Sparse B-spline polynomial descriptors for human activity recognition
Image and Vision Computing
Likelihood tuning for particle filter in visual tracking
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptive particle filter based on energy field for robust object tracking in complex scenes
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
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We present a nonlinear state estimation approach using particle filters, for tracking objects whose approximate 3D shapes are known. The unnormalized conditional density for the solution to the nonlinear filtering problem leads to the Zakai equation, and is realized by the weights of the particles. The weight of a particle represents its geometric and temporal fit, which is computed bottom-up from the raw image using a shape-encoded filter. The main contribution of the paper is the design of smoothing filters for feature extraction combined with the adoption of unnormalized conditional density weights. The "shape filter" has the overall form of the predicted 2D projection of the 3D model, while the cross-section of the filter is designed to collect the gradient responses along the shape. The 3D-model-based representation is designed to emphasize the changes in 2D object shape due to motion, while de-emphasizing the variations due to lighting and other imaging conditions. We have found that the set of sparse measurements using a relatively small number of particles is able to approximate the high-dimensional state distribution very effectively. As a measure to stabilize the tracking, the amount of random diffusion is effectively adjusted using a Kalman updating of the covariance matrix. For a complex problem of human body tracking, we have successfully employed constraints derived from joint angles and walking motion.