—This paper presents methods of modeling and predicting face recognition (FR) system performance based on analysis of similarity scores. We define the performance of an FR system...
—This paper presents a new framework for the completion of missing information based on local structures. It poses the task of completion as a global optimization problem with a ...
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
—The analysis of periodic or repetitive motions is useful in many applications, such as the recognition and classification of human and animal activities. Existing methods for th...
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
—We develop a mathematical framework for quantifying and understanding multidimensional frequency modulations in digital images. We begin with the widely accepted definition of t...
—We present a novel space-time patch-based method for image sequence restoration. We propose an adaptive statistical estimation framework based on the local analysis of the bias-...
—We introduce a new general framework for the recognition of complex visual scenes, which is motivated by biology: We describe a hierarchical system that closely follows the orga...
Thomas Serre, Lior Wolf, Stanley M. Bileschi, Maxi...