Compressive Sensing (CS) uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compressible signals. The Hough t...
Ali Cafer Gurbuz, James H. McClellan, Justin K. Ro...
Abstract— In this paper, we present a novel universal approach which consists in exploring statistics in the compressed frequency domain. This approach is motivated by two main c...
Johann Barbier, Eric Filiol, Kichenakoumar Mayoura
This paper presents a system for video object generation and selective encoding with applications in surveillance, mobile videophones, and automotive industry. Object tracking and...
Alessio Del Bue, Dorin Comaniciu, Visvanathan Rame...
Recognition algorithms that use data obtained by imaging faces in the thermal spectrum are promising in achieving invariance to extreme illumination changes that are often present...
Ognjen Arandjelovic, Riad I. Hammoud, Roberto Cipo...
In this paper, we propose an approach to learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in vide...