The recognition of nonrigid motion, particularly that arising from human movement (and by extension from the locomotory activity of animals) has typically made use of high-level parametric models representing the various body parts (legs, arms, trunk, head etc.) and their connections to each other. Such model-based recognition has been successful in some cases; however, the methods are often di...

...................................................................................................................... iii Preface........................................................................................................................... v Acknowledgments................................................................................................... vii

There has been a recent and increasing interest in computer analysis and recognition of human motion. Previously we presented an efficient real-time approach for representing human motion using a compact “Motion History Image” (MHI). Recognition was achieved by statistically matching moment-based features. To address previous problems related to global analysis and limited recognition, we prese...

In this paper we present an algorithm for recogniz ing walking pedestrians in sequences of color images taken from a moving camera The recognition is based on the characteristic motion of the legs of a pedestrian walking parallel to the image plane Each image is seg mented into region like image parts by clustering pixels in a combined color position feature space The pro posed clustering techn...

The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are ea...

A novel framework based on action recognition feedback for pose reconstruction of articulated human body from monocular images is proposed in this paper. The intrinsic ambiguity caused by perspective projection makes it difficult to accurately recover articulated poses from monocular images. To alleviate such ambiguity, we exploit the high-level motion knowledge as action recognition feedback t...

Motion trajectories have been widely used for gesture recognition. An effective representation of 3D motion trajectory is important for capturing and recognizing complex motion patterns. In this paper, we propose a view invariant hierarchical parsing method for free form 3D motion trajectory representation. The raw motion trajectory is first parsed into four types of trajectory primitives based...

The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are ea...

People move in characteristic ways during conversation and these movements correlate with their level of particpation. For example, speakers normally gesture significantly more than listeners. These visible, overt movements are normally analysed using full body video or motion capture. Here we explore the potential of a ’minimal’ approach to sensing these participatory movements in part of the ...