The problem of low-rank matrix factorization in the presence of missing data has seen significant attention in recent computer vision research. The approach that dominates the lit...
Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent ad...
We present a novel stochastic, adaptive strategy for tracking multiple people in a large network of video cameras. Similarities between features (appearance and biometrics) observ...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
We present a method for extracting dense features from stereo and motion sequences. Our dense feature is defined symmetrically with respect to both images, and it is extracted dur...