In this paper, we present a method based on tangent distance to estimate motion in image sequences. Tangent distance combines an intuitive understanding and effective modeling of ...
Enabling and managing coordination activities between autonomous, possibly mobile, computing entities in dynamic computing scenarios challenges traditional approaches to distribut...
We present an unsupervised approach for learning a generative layered representation of a scene from a video for motion segmentation. The learnt model is a composition of layers, ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
Motion planning for humanoids faces several challenging issues: high dimensionality of the configuration space, necessity to address balance constraints in single and double suppo...
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...