Title :
Co-recognition of Actions in Video Pairs
Author :
Shin, Young Min ; Cho, Minsu ; Lee, Kyoung Mu
Author_Institution :
Dept. of EECS, Seoul Nat. Univ., Seoul, South Korea
Abstract :
In this paper, we present a method that recognizes single or multiple common actions between a pair of video sequences. We establish an energy function that evaluates geometric and photometric consistency, and solve the action recognition problem by optimizing the energy function. The proposed stochastic inference algorithm based on the Monte Carlo method explores the video pair from the local spatio-temporal interest point matches to find the common actions. Our algorithm works in unsupervised way without prior knowledge about the type and the number of common actions. Experiments show that our algorithm produces promising results on single and multiple action recognition.
Keywords :
Monte Carlo methods; image recognition; image sequences; inference mechanisms; video signal processing; Monte Carlo method; action recognition; energy function; geometric consistency; photometric consistency; spatio-temporal interest point matches; stochastic inference algorithm; video sequence pairs; Accuracy; Clustering algorithms; Humans; Markov processes; Monte Carlo methods; Shape; Video sequences; action recognition; co-recognition; computer vision;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.120