Low-dimensional representations of sensory signals are key to solving many of the computational problems encountered in high-level vision. Principal Component Analysis (PCA) has b...
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear sim...
While computing power and transmission bandwidth have both been steadily increasing over the last few years, bandwidth rather than processing power remains the primary bottleneck f...
—Keypoints on 3D surfaces are points that can be extracted repeatably over a wide range of 3D imaging conditions. They are used in many 3D shape processing applications; for exam...
Partially occluded faces are common in many applications
of face recognition. While algorithms based on sparse
representation have demonstrated promising results, they
achieve t...
Zihan Zhou, Andrew Wagner, Hossein Mobahi, John Wr...