Title :
The Framework of Infrared Video Mining Based on Topic Model
Author :
Lin Liu ; Lin Tang ; Hong Li ; Shaowen Yao
Author_Institution :
Yunnan Univ., Kunming, China
Abstract :
We proposed a framework of infrared video mining based on topic model. It aims to learn motion patterns for a crowded and complicated infrared scene. After video preprocessing, motion features are extracted from each pair of consecutive frames at first, and quantized into visual words. Motion pattern are modeled as distributions over visual words in topic model. Experiments about BOVW demonstrate the feasibility of the framework.
Keywords :
data mining; feature extraction; image motion analysis; infrared imaging; video signal processing; BOVW; infrared scene; infrared video mining; motion feature extraction; motion patterns; topic model; video preprocessing; visual words; Computational modeling; Computer vision; Feature extraction; Hidden Markov models; Image motion analysis; Optical imaging; Visualization; BOVW; infrared video; motion pattern; topic model;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2014 Sixth International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-4956-4
DOI :
10.1109/IHMSC.2014.187
