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VISUAL TRACKING AND RECOGNITION OF THE HUMAN HAND

  • Kartonierter Einband
  • 108 Seiten
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Most of the computer-vision-based hand gesture recognition systems are either confined to a fixed set of static gestures or only a... Weiterlesen
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Beschreibung

Most of the computer-vision-based hand gesture recognition systems are either confined to a fixed set of static gestures or only able to track 2D global hand motion. In order to recognize natural hand gestures such as those in American sign language, we need to track articulated hand motion in real time. The task is challenging due to the high degrees of freedom of the hand, self-occlusion, variable views, and lighting. This book focuses on automatic recovery of 3D hand motion from one or more views. The problem of hand tracking is formulated as Bayesian filtering in the framework of analysis-by-synthesis. We propose an Eigen Dynamic Analysis model and a new feature called likelihood edge. To automatically initialize and recover from loss-track, we proposed a bottom-up posture recognition algorithm. It collectively matches the local features in a single image with those in the image database. Through quantitative and visual experimental results, we demonstrate the effectiveness of our approach and point out its limitations.

Autorentext

Hanning Zhou is a senior manager in Amazon Media Technology Group.Prior to Amazon, he worked on video surveillance in FX Palo AltoLab (FXPAL) as a research scientist.As an undergrad from Tsinghua Univ., he worked with Harry Shum inMS Research Asia on video compression.He received PhD from Univ. of Illinois Urbana Champaign and held12 patents.



Klappentext

Most of the computer-vision-based hand gesturerecognition systems are either confined to a fixedset of static gestures or only able to track 2Dglobal hand motion. In order to recognize natural hand gestures such asthose in American sign language, we need to trackarticulated hand motion in real time. The task ischallenging due to the high degrees of freedom of thehand, self-occlusion, variable views, and lighting. This book focuses on automatic recovery of 3D handmotion from one or more views.The problem of hand tracking is formulated asBayesian filtering in the framework ofanalysis-by-synthesis. We propose an Eigen DynamicAnalysis model and a new feature called likelihood edge. To automatically initialize and recover fromloss-track, we proposed a bottom-up posturerecognition algorithm. It collectively matches thelocal features in a single image with those in theimage database. Through quantitative and visualexperimental results, we demonstrate theeffectiveness of our approach and point out itslimitations.

Produktinformationen

Titel: VISUAL TRACKING AND RECOGNITION OF THE HUMAN HAND
Untertitel: Combining Top-down Synthesis with Bottom-up Analysis
Autor:
EAN: 9783639153859
ISBN: 978-3-639-15385-9
Format: Kartonierter Einband
Herausgeber: VDM Verlag
Genre: Sonstiges
Anzahl Seiten: 108
Gewicht: 179g
Größe: H221mm x B151mm x T12mm
Veröffentlichung: 01.05.2009
Jahr: 2009