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CVPR
2010
IEEE
16 years 1 months ago
Learning a Hierarchy of Discriminative Space-Time Neighborhood Features for Human Action Recognition
Recent work shows how to use local spatio-temporal features to learn models of realistic human actions from video. However, existing methods typically rely on a predefined spatial...
Adriana Kovashka, Kristen Grauman
HUMO
2007
Springer
15 years 11 months ago
Semi-Latent Dirichlet Allocation: A Hierarchical Model for Human Action Recognition
We propose a new method for human action recognition from video sequences using latent topic models. Video sequences are represented by a novel “bag-of-words” representation, w...
Yang Wang 0003, Payam Sabzmeydani, Greg Mori
CVPR
2008
IEEE
16 years 7 months ago
Learning human actions via information maximization
In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a ba...
Jingen Liu, Mubarak Shah
ICCV
2003
IEEE
16 years 7 months ago
Recognizing Human Action Efforts: An Adaptive Three-Mode PCA Framework
We present a computational framework capable of labeling the effort of an action corresponding to the perceived level of exertion by the performer (low ? high). The approach initi...
James W. Davis, Hui Gao
AVSS
2007
IEEE
15 years 12 months ago
Compact representation and probabilistic classification of human actions in videos
This paper addresses the problem of classifying human actions in a video sequence. A representation eigenspace approach based on the PCA algorithm is used to train the classifier...
Carlo Colombo, Dario Comanducci, Alberto Del Bimbo