We propose a model-based tracking method, called appearance-guided particle filtering (AGPF), which integrates both sequential motion transition information and appearance informa...
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
A new particle filter, Kernel Particle Filter (KPF), is proposed for visual tracking for multiple objects in image sequences. The KPF invokes kernels to form a continuous estimate...
Prior work has argued that when a Lambertian surface in fixed pose is observed in multiple images under varying distant illumination, there is an equivalence class of surfaces giv...
Manmohan Krishna Chandraker, Fredrik Kahl, David J...
We present a particle filtering algorithm for robustly tracking the contours of multiple deformable objects through severe occlusions. Our algorithm combines a multiple blob track...