Multiple view geometry in computer vision
Multiple view geometry in computer vision
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
A decision based one-against-one method for multi-class support vector machine
Pattern Analysis & Applications
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Applying 3D human model in a posture recognition system
Pattern Recognition Letters
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Human posture tracking and classification through stereo vision and 3D model matching
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
Linear-projection-based classification of human postures in time-of-flight data
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Activities as time series of human postures
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
CC-RANSAC: Fitting planes in the presence of multiple surfaces in range data
Pattern Recognition Letters
Real-time human pose recognition in parts from single depth images
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Probabilistic posture classification for Human-behavior analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Human action recognition based on skeleton splitting
Expert Systems with Applications: An International Journal
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A non-invasive system for human posture recognition suitable to be used in several in-home scenarios is proposed and validation results presented. 3D point cloud sequences were acquired by using a time-of-flight sensor in a privacy preserving modality and near real-time processed with a low power embedded PC. To satisfy different application requirements in terms of discrimination capabilities, covered distance range and processing speed, a twofold discrimination approach was investigated in which features were hierarchical arranged from coarse to fine exploiting both topological and volumetric spatial representations. The topological representation encoded the intrinsic topology of the body's shape in a skeleton-based structure, guarantying invariance to scale, rotations and postural changes, and achieving a high level of detail with a moderate computational cost. In the volumetric representation, on the other hand, postures were described in terms of 3D cylindrical histograms working within a wider range of distances in a faster way and also guarantying good invariance properties. The discrimination capabilities of the approach were evaluated in four different real-home scenarios especially related with ambient assisted living and homecare fields, namely dangerous event detection, anomalous behavior detection, activities recognition, natural human-ambient interaction, and also in terms of invariance to viewpoint changes, representation capabilities and classification performance, achieving promising results. The two approaches exhibited complementary characteristics showing high reliability with classification rates greater than 97% in four application scenarios for which the posture recognition is a fundamental function.