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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 30 / No. 1: Thirtieth AAAI Conference On Artificial Intelligence

Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain

March 8, 2023

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Authors

Donghun Yeo

POSTECH


Bohyung Han

POSTECH


Joon Hee Han

POSTECH


DOI:

10.1609/aaai.v30i1.10464


Abstract:

We propose a simple but effective unsupervised learning algorithm to detect a common activity (co-activity) from a set of videos, which is formulated using absorbing Markov chain in a principled way. In our algorithm, a complete multipartite graph is first constructed, where vertices correspond to subsequences extracted from videos using a temporal sliding window and edges connect between the vertices originated from different videos; the weight of an edge is proportional to the similarity between the features of two end vertices. Then, we extend the graph structure by adding edges between temporally overlapped subsequences in a video to handle variable-length co-activities using temporal locality, and create an absorbing vertex connected from all other nodes. The proposed algorithm identifies a subset of subsequences as co-activity by estimating absorption time in the constructed graph efficiently. The great advantage of our algorithm lies in the properties that it can handle more than two videos naturally and identify multiple instances of a co-activity with variable lengths in a video. Our algorithm is evaluated intensively in a challenging dataset and illustrates outstanding performance quantitatively and qualitatively.

Topics: AAAI

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HOW TO CITE:

Donghun Yeo|| Bohyung Han|| Joon Hee Han Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain Proceedings of the AAAI Conference on Artificial Intelligence, 30 (2016) .

Donghun Yeo|| Bohyung Han|| Joon Hee Han Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain AAAI 2016, .

Donghun Yeo|| Bohyung Han|| Joon Hee Han (2016). Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain. Proceedings of the AAAI Conference on Artificial Intelligence, 30, .

Donghun Yeo|| Bohyung Han|| Joon Hee Han. Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain. Proceedings of the AAAI Conference on Artificial Intelligence, 30 2016 p..

Donghun Yeo|| Bohyung Han|| Joon Hee Han. 2016. Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain. "Proceedings of the AAAI Conference on Artificial Intelligence, 30". .

Donghun Yeo|| Bohyung Han|| Joon Hee Han. (2016) "Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain", Proceedings of the AAAI Conference on Artificial Intelligence, 30, p.

Donghun Yeo|| Bohyung Han|| Joon Hee Han, "Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain", AAAI, p., 2016.

Donghun Yeo|| Bohyung Han|| Joon Hee Han. "Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain". Proceedings of the AAAI Conference on Artificial Intelligence, 30, 2016, p..

Donghun Yeo|| Bohyung Han|| Joon Hee Han. "Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain". Proceedings of the AAAI Conference on Artificial Intelligence, 30, (2016): .

Donghun Yeo|| Bohyung Han|| Joon Hee Han. Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain. AAAI[Internet]. 2016[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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Artificial Intelligence 1900 Embarcadero Road, Suite
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