A number of accounts of human auditory perception assume that listeners use prior stimulus context to generate predictions about future stimulation. Here, we tested an auditory pitch-motion hypothesis that was developed from this perspective. Listeners judged either the time change (i.e., duration

; Wiesel 1968, DeValois et al. 1982a, DeAngelis et al. 1993): they are localised in space and time, have band-pass characteristics in the spatial and temporal frequency domains, are oriented, and are often sensitive to the direction of motion of a stimulus. Here we will concentrate on the spatial

Predicting motion hypothesis from poses

We describe a vision system that monitors activity in a site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive tracker detects multiple moving objects in the sensors. Our hypothesis is that motion tracking is sufficient to support a range

mode switching for multi-hypothesis

Motion correspondence is a fundamental problem in computer vision and many other disciplines. This article describes statistical data association techniques originally developed in the context of target tracking and surveillance and now beginning to be used in dynamic motion analysis

as color, orientation and motion), and provides optimal solutions for many other saliency problems of interest for computer vision. Optimal solutions, under this hypothesis, are derived for a number of the former (including static natural images, dense motion fields, and even dynamic textures), and applied

photoreceptors within the integration time of the receptors, yet usually, no motion blur is experienced. An elegant model for the elimination of motion blur was proposed by Anderson and vanEssen (1987) who suggested that the neuronal representation of the retinal image is shifted on its way

In this paper, we propose a long-term motion model for visual object tracking. In crowded street scenes, persistent occlusions are a frequent challenge for tracking algorithm and a robust, long-term motion model could help in these situations. Motivated by progresses in robot motion planning, we

An emerging literature has begun to document the affective consequences of emotion regulation. Little is known, however, about whether motion regulation also has cognitive consequences. A process model of emotion suggests hat expressive suppression should reduce memory for emotional events