Abstract. In this paper we review the major approaches to multimodal human computer interaction from a computer vision perspective. In particular, we focus on body, gesture, gaze, ...
Contemporary face recognition algorithms rely on precise
localization of keypoints (corner of eye, nose etc.). Unfortunately,
finding keypoints reliably and accurately remains
a...
The paper introduces an action recognition framework that uses concepts from the theory of chaotic systems to model and analyze nonlinear dynamics of human actions. Trajectories o...
A probabilistic system for recognition of individual objects is presented. The objects to recognize are composed of constellations of features, and features from a same object shar...
In this paper, we address the problem of learning compact, view-independent, realistic 3D models of human actions recorded with multiple cameras, for the purpose of recognizing th...