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CVPR
2008
IEEE
14 years 9 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
TCSV
2008
175views more  TCSV 2008»
13 years 7 months ago
Expandable Data-Driven Graphical Modeling of Human Actions Based on Salient Postures
This paper presents a graphical model for learning and recognizing human actions. Specifically, we propose to encode actions in a weighted directed graph, referred to as action gra...
Wanqing Li, Zhengyou Zhang, Zicheng Liu
ICCV
2011
IEEE
12 years 7 months ago
Human Action Recognition by Learning Bases of Action Attributes and Parts
In this work, we propose to use attributes and parts for recognizing human actions in still images. We define action attributes as the verbs that describe the properties of human...
Bangpeng Yao, Xiaoye Jiang, Aditya Khosla, Andy La...
CVPR
2006
IEEE
14 years 9 months ago
Automatic Discovery of Action Taxonomies from Multiple Views
We present a new method for segmenting actions into primitives and classifying them into a hierarchy of action classes. Our scheme learns action classes in an unsupervised manner ...
Daniel Weinland, Rémi Ronfard, Edmond Boyer
CVPR
2010
IEEE
14 years 1 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia