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» Learning and Recognizing Human Dynamics in Video Sequences
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ECCV
2010
Springer
14 years 10 months ago
Activities as Time Series of Human Postures
Abstract. This paper presents an exemplar-based approach to detecting and localizing human actions, such as running, cycling, and swinging, in realistic videos with dynamic backgro...
William Brendel, Sinisa Todorovic
CVPR
2008
IEEE
15 years 11 months ago
Learning 4D action feature models for arbitrary view action recognition
In this paper we present a novel approach using a 4D (x,y,z,t) action feature model (4D-AFM) for recognizing actions from arbitrary views. The 4D-AFM elegantly encodes shape and m...
Pingkun Yan, Saad M. Khan, Mubarak Shah
CVPR
2007
IEEE
15 years 11 months ago
Marker-less Deformable Mesh Tracking for Human Shape and Motion Capture
We present a novel algorithm to jointly capture the motion and the dynamic shape of humans from multiple video streams without using optical markers. Instead of relying on kinemat...
Edilson de Aguiar, Christian Theobalt, Carsten Sto...
ICVGIP
2004
14 years 11 months ago
Markerless Motion Capture from Monocular Videos
We present a method to determine the 3D spatial locations of joints of a human body from a monocular video sequence of a Bharatanatyam dance. The proposed method uses domain speci...
Vishal Mamania, Appu Shaji, Sharat Chandran
CVPR
2008
IEEE
15 years 11 months ago
Action recognition using exemplar-based embedding
In this paper, we address the problem of representing human actions using visual cues for the purpose of learning and recognition. Traditional approaches model actions as space-ti...
Daniel Weinland, Edmond Boyer