This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
The loss of information due to occlusion and other complications has been one of the main bottlenecks in the field of motion estimation. In this paper, we propose a novel motion e...
New representations are developed for 2D IP (implicit polynomial) curves ofarbitrary degree. These representations permit shape recognition and pose estimation with essentially sin...
This essay draws on participant observation, ethnographic interviews, phenomenological inquiry, and recent insights from the study of swarm intelligence and complex networks to ill...
Abstract. In this study we show that humans are able to form a perceptual space from a complex, three-dimensional shape space that is highly congruent to the physical object space ...