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Human Action Analysis with Randomized Trees

Part of the SpringerBriefs in Electrical and Computer Engineering Book Series

DOI: 10.1007/978-981-287-167-1

ISBN: 978-981-287-166-4

Publisher: Springer Singapore - Springer Journals

Aug 15, 2014

Available

Introduction to Human Action Analysis

Yu, Gang; Yuan, Junsong; Liu, Zicheng

Pages: 1 –8

[Human action analysis plays a critical role in human centered computing, as in many applications we require to analyze and understand human actions in the big video data, such as video surveillance, health care and human–computer interaction. In this chapter, we start from an overview of human...
Available

Supervised Trees for Human Action Recognition and Detection

Yu, Gang; Yuan, Junsong; Liu, Zicheng

Pages: 9 –27

[Efficient action detection in unconstrained videos is as challenging problem due to the cluttered backgrounds and the large intra-class variations of human actions. In this chapter, we characterize a video as a collection of spatio-temporal interest points, and locate actions via searching for...
Available

Unsupervised Trees for Human Action Search

Yu, Gang; Yuan, Junsong; Liu, Zicheng

Pages: 29 –56

[Action search is an interesting problem for human action analysis, which has a lot of potential applications in industry. In this chapter, we propose a very fast action retrieval system which can effectively locate the subvolumes similar to the query video. Random-indexing-trees-based visual...
Available

Propagative Hough Voting to Leverage Contextual Information

Yu, Gang; Yuan, Junsong; Liu, Zicheng

Pages: 57 –72

[Generalized Hough voting has shown promising results in both object and action detection. However, most existing Hough voting methods will suffer when insufficient training data are provided. To address this limitation, we propose propagative Hough voting in this chapter. Instead of training a...
Available

Human Action Prediction with Multiclass Balanced Random Forest

Yu, Gang; Yuan, Junsong; Liu, Zicheng

Pages: 73 –81

[Early recognition and prediction of human activities are of great importance in video surveillance. In this chapter, we target this problem by developing a spatial-temporal implicit shape model (STISM), which characterizes the space-time structure of the sparse local features extracted from a...
Available

Conclusion

Yu, Gang; Yuan, Junsong; Liu, Zicheng

Pages: 83 –83

[Generally, this book provides a systematic study on the human action analysis problems based on tree-based approaches. This chapter concludes the four approaches presented in this book.]

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