Three-Dimensional Motion Estimation of Objects for Video Coding
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We investigated how the visual system selects a reference frame for the perception of motion. Two concentric arcs underwent circular motion around the center of the display, where observers fixated. The outer (target) arc's angular velocity profile was mod ...
Association for Research in Vision and Ophthalmology (ARVO)2016
A reference frame is required to specify how motion is perceived. For example, the motion of part of an object is usually perceived relative to the motion of the object itself. Johansson (Psychological Research, 38, 379-393, 1976) proposed that the percept ...
The retinotopic projection of stimulus motion depends both on the motion of the stimulus and the movements of the observer. In this study, we aimed to quantify the contributions of endogenous (retinotopic) and exogenous (spatiotopic and motion-based) refer ...
Many visual attributes of a target stimulus are computed according to dynamic, non-retinotopic reference frames. For example, the motion trajectory of a reflector on a bicycle wheel is perceived as orbital, even though it is in fact cycloidal in retinal, a ...
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We propose a variational aggregation method for optical flow estimation. It consists of a two-step framework, first estimating a collection of parametric motion models to generate motion candidates, and then reconstructing a global dense motion field. The ...
Conventional motion estimation algorithms extract motion vectors from image sequences based on the image's local-brightness differences in consecutive images. Therefore, motion vectors are extracted along the moving edges formed by moving objects over thei ...
We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people. Previous approaches typically compute candidate poses in individual frames and then link them in a post-processi ...
We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown support, and evolve over time according to a generic nonlinear dynamical model. O ...
Institute of Electrical and Electronics Engineers2016
We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown support, and evolve over time according to a generic nonlinear dynamical model. O ...
Institute of Electrical and Electronics Engineers2016
