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A Framework for Event Classification from Video Sequences using Bayesian Neural Network
| Communications on Applied Electronics |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 5 - Number 2 |
| Year of Publication: 2016 |
| Authors: Putte Gowda D., Padma M. C. |
10.5120/cae2016652229
|
Putte Gowda D., Padma M. C. . A Framework for Event Classification from Video Sequences using Bayesian Neural Network. Communications on Applied Electronics. 5, 2 ( May 2016), 1-5. DOI=10.5120/cae2016652229
Abstract
Due to immense growth happened in multimedia field, research with videos and images have been received significant attention among the researchers. The automatic detection of the events presented in the video content may provide more useful information to the target audience. The motivation behind this approach is to design and develop a system for video event classification through video content analysis method using Bayesian neural network. Initially, the background from the video frames is estimated which is then segmented. Subsequently, features are extracted from the tracked objects and are classified to normal or abnormal event by applying Bayesian neural network classifier.UCSD Anomaly Detection Datasets is used for implementation. The performance of the proposed system is validated through the ROC curves and classification accuracy. From the comparative analysis made, the proposed technique obtained better results.
References
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