Corpus ID: 85439346

Unsupervised Learning of Human Action Categories

@inproceedings{Niebles2006UnsupervisedLO,
  title={Unsupervised Learning of Human Action Categories},
  author={Juan Carlos Niebles and Hongcheng Wang and Li Fei-Fei},
  year={2006}
}
Imagine a video taken on a sunny beach, can a computer automatically tell what is happening in the scene? Can it identify different human activities in the video, such as water surfing, people walking and lying on the beach? To automatically classify or localize different actions in video sequences is very useful for a variety of tasks, such as video surveillance, objectlevel video summarization, video indexing, digital library organization, etc. However, it remains a challenging task for… Expand
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References

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Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
TLDR
The approach is not only able to classify different actions, but also to localize different actions simultaneously in a novel and complex video sequence. Expand
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words
TLDR
A novel unsupervised learning method for human action categories that can recognize and localize multiple actions in long and complex video sequences containing multiple motions. Expand
Recognizing human actions: a local SVM approach
TLDR
This paper construct video representations in terms of local space-time features and integrate such representations with SVM classification schemes for recognition and presents the presented results of action recognition. Expand
Unsupervised Discovery of Action Classes
TLDR
This paper will attack the problem of describing the action being performed by human figures in still images using an unsupervised learning approach, attempting to discover the set of action classes present in a large collection of training images. Expand