Human Motion - Understanding, Modeling, Capture and Animation : Second Workshop, HumanMotion 2007, Rio de Janeiro, Brazil, October 20, 2007, Proceedings / edited by Ahmed Elgammal, Bodo Rosenhahn, Reinhard Klette.

Format:

Book

Contributor:

Elgammal, Ahmed, editor.

Rosenhahn, Bodo, editor.

Klette, Reinhard, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 4814.

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 4814

Language:

English

Subjects (All):

Optical data processing.

Computer simulation.

Artificial intelligence.

Bioinformatics.

Biometry.

Image Processing and Computer Vision.

Simulation and Modeling.

Artificial Intelligence.

Computational Biology/Bioinformatics.

Biometrics.

Local Subjects:

Image Processing and Computer Vision.

Simulation and Modeling.

Artificial Intelligence.

Computational Biology/Bioinformatics.

Biometrics.

Physical Description:

1 online resource (X, 332 pages).

Edition:

First edition 2007.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2007.

System Details:

text file PDF

Summary:

This LNCS volume contains the papers presented at the second Workshop on Human Motion Understanding, Modeling, Capture and Animation, which took place on October 20th, 2007, accompanying the 11th IEEE International C- ference on Computer Vision in Rio de Janeiro, Brazil. In total, 38 papers were submitted to this workshop,of which 22 papers were accepted. We were careful to ensure a high standard of quality when selecting the papers. All submissions were double-blind reviewed by at least two experts. Out of the 22 accepted papers, 10 were selected for oral presentation and 12 for posters. We thank the authors of the accepted papers for taking the reviewers' comments into account in the ?nal published versions of their papers. We thank all of the authors who submitted their work, and we trust that the reviewers' comments have been of value for their research activities. The accepted papers re?ect the state of the art in the ?eld and cover various topicsrelatedto humanmotiontrackingandanalysis.Thepapersinthisvolume have been classi?ed into three categories based on the topics they cover: human motion capture and pose estimation, body and limb tracking and segmentation, and activity recognition.

Contents:

Motion Capture and Pose Estimation

Marker-Less 3D Feature Tracking for Mesh-Based Human Motion Capture

Boosted Multiple Deformable Trees for Parsing Human Poses

Gradient-Enhanced Particle Filter for Vision-Based Motion Capture

Multi-activity Tracking in LLE Body Pose Space

Exploiting Spatio-temporal Constraints for Robust 2D Pose Tracking

Efficient Upper Body Pose Estimation from a Single Image or a Sequence

Real-Time and Markerless 3D Human Motion Capture Using Multiple Views

Modeling Human Locomotion with Topologically Constrained Latent Variable Models

Silhouette Based Generic Model Adaptation for Marker-Less Motion Capturing

Body and Limb Tracking and Segmentation

3D Hand Tracking in a Stochastic Approximation Setting

Nonparametric Density Estimation with Adaptive, Anisotropic Kernels for Human Motion Tracking

Multi Person Tracking Within Crowded Scenes

Joint Appearance and Deformable Shape for Nonparametric Segmentation

Robust Spectral 3D-Bodypart Segmentation Along Time

Articulated Object Registration Using Simulated Physical Force/Moment for 3D Human Motion Tracking

An Ease-of-Use Stereo-Based Particle Filter for Tracking Under Occlusion

Activity Recognition

Semi-Latent Dirichlet Allocation: A Hierarchical Model for Human Action Recognition

Recognizing Activities with Multiple Cues

Human Action Recognition Using Distribution of Oriented Rectangular Patches

Human Motion Recognition Using Isomap and Dynamic Time Warping

Behavior Histograms for Action Recognition and Human Detection

Learning Actions Using Robust String Kernels.

Other Format:

Printed edition:

ISBN:

978-3-540-75703-0

9783540757030

Access Restriction:

Restricted for use by site license.