Human Motion - Understanding, Modeling, Capture and Animation

Second Workshop, HumanMotion 2007, Rio de Janeiro, Brazil, October 20, 2007, Proceedings
2007
ISBN: 978-3-540-75702-3
Verlag: Springer Berlin Heidelberg

Buch, Englisch, Band 4814, 332 Seiten, Book w. online files / update, Format (B × H): 155 mm x 235 mm, Gewicht: 522 g

Reihe: Lecture Notes in Computer Science

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.

Zielgruppe

Research

Autoren/Hrsg.

Elgammal, Ahmed

Klette, Reinhard

Rosenhahn, Bodo

Fachgebiete

• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Naturwissenschaften Biowissenschaften Biowissenschaften
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Grafikprogrammierung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Datensicherheit, Datenschutz
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik

Inhaltsverzeichnis

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.