Title :
Activity recognition in thermal infrared video
Author :
Hossen, Jakir ; Jacobs, Eddie L. ; Chowdhury, Fahmida Kishowara
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Memphis, Memphis, TN, USA
Abstract :
In this paper, we investigate the tracking and recognition of limited activity in thermal infrared video. We have improved the pose segmentation from the background using a universal segmentation technique. Gait energy images (GEI) have been developed for collected repetitive and non-repetitive activities. Seven invariant moments features are extracted from the sequences of GEI of each activity and concatenated to a feature vector. Naïve Bayesians classifier is used for classification of feature vectors. Experimental result on limited activity shows the effectiveness of our proposed activity recognition algorithm.
Keywords :
Bayes methods; image segmentation; infrared imaging; object recognition; pattern classification; pose estimation; video signal processing; GEI; activity recognition; feature vector; gait energy images; invariant moments features; naïve Bayesians classifier; nonrepetitive activities; pose segmentation; repetitive activities; thermal infrared video; universal segmentation technique; Bayes methods; Cameras; Computer vision; Feature extraction; Image segmentation; Motion segmentation; Surveillance; activity recognition; principle component analysis; segmentation; thermal infrared video; tracking;
Conference_Titel :
SoutheastCon 2015
Conference_Location :
Fort Lauderdale, FL
DOI :
10.1109/SECON.2015.7132922
