Authors:
Hildegard Kuehne
and
Annika Woerner
Affiliation:
Institute for Algorithms and Cognitive Systems, University Karlsruhe(TH), Germany
Keyword(s):
Feature clustering, Motion principles, Articulated body tracking, Body structure reconstruction, Feature tracking, Motion analysis.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Detecting 3D Objects Using Patterns of Motion and Appearance
;
Feature Extraction
;
Features Extraction
;
Human-Computer Interaction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Signal Processing, Sensors, Systems Modeling and Control
;
Stereo Vision and Structure from Motion
Abstract:
The recovery of three dimensional structures from moving elements is one of the main abilities of the human perception system. It is mainly based on particularities of how we interpret moving features, especially on the enforcement of geometrical grouping and definition of relation between features. In this paper we evaluate how the human abilities of motion based feature clustering can be transferred to an algorithmic approach to determine the structure of a rigid or articulated body in an image sequence. It shows how to group sparse 3D motion features to structural clusters, describing the rigid elements of articulated body structures. The location and motion properties of sparse feature point clouds have been analyzed and it is shown that moving features can be clustered by their local and temporal properties without any additional image information. The assembly of these structural groups could allow the detection of a human body in an image as well as its pose estimation. So, su
ch a clustering can establish a basis for a markerless reconstruction of articulated body structures as well as for human motion recognition by moving features.
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