Title :
Classifying bags of keypoints using HMMs
Author :
Zaklouta, Fatin ; Stanciulescu, Bogdan
Author_Institution :
Mines ParisTech, Paris, France
Abstract :
In this paper, we use a Hidden Markov Models (HMM) to classify bags of SURF keypoints descriptors of a given class. The performance of this technique is compared to that of others, by testing it on various multi-class datasets. We also describe a prospective of expanding our application to include the detection and classification of moving objects in a video stream using optical flow and Self Organizing Maps (SOM).
Keywords :
hidden Markov models; image classification; video streaming; HMM; SURF bag; hidden markov model; moving objects classification; moving objects detection; multiclass dataset; optical flow; self organizing map; video stream; Accuracy; Feature extraction; Hidden Markov models; Kernel; Robustness; Streaming media; Training; Hidden Markov Models; Multi-class; SURF; bag of features; classification; keypoints;
Conference_Titel :
Computer Systems and Applications (AICCSA), 2010 IEEE/ACS International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4244-7716-6
DOI :
10.1109/AICCSA.2010.5587039
