Thursday 25th of April 2024
 

Intelligent Video Object Classification Scheme using Offline Feature Extraction and Machine Learning based Approach


Chandra Mani Sharma, Alok Kumar Singh Kushwaha, Rakesh Roshan, Rabins Porwal and Ashish Khare

Classification of objects in video stream is important because of its application in many emerging areas such as visual surveillance, content based video retrieval and indexing etc. The task is far more challenging because the video data is of heavy and highly variable nature. The processing of video data is required to be in real-time. This paper presents a multiclass object classification technique using machine learning approach. Haar-like features are used for training the classifier. The feature calculation is performed using Integral Image representation and we train the classifier offline using a Stage-wise Additive Modeling using a Multiclass Exponential loss function (SAMME). The validity of the method has been verified from the implementation of a real-time human-car detector. Experimental results show that the proposed method can accurately classify objects, in video, into their respective classes. The proposed object classifier works well in outdoor environment in presence of moderate lighting conditions and variable scene background. The proposed technique is compared, with other object classification techniques, based on various performance parameters.

Keywords: Object Classification, Machine Learning, Real-time Video Processing, Visual Surveillance

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ABOUT THE AUTHORS

Chandra Mani Sharma
Chandra Mani Sharma received his B.Sc. from Meerut College in 2006, MCA in year 2009 from ITS Ghaziabad and M.Tech. in Computer Science from Devi Ahilya University, Indore in year 2011. He worked as a research fellow on UGC-Sponsored research project An Intelligent Video Surveillance System for Human Behavior Analysis at IPCV Labs, University of Allahabad from May, 2010 to June, 2011. He has obtained various awards and scholarships including ITS-meritorious scholarship, IETE scholarship and MHRD-India scholarship. Currently, he is holding the position of assistant professor in IT at ITS Ghaziabad, India.

Alok Kumar Singh Kushwaha
Alok Kumar Singh Kushwaha received his B.Sc. and M.Sc. from University of Allahabd. He has done his M.Tech in Software Engineering from Devi Ahilya University, Indore in 2011. He is working as an assistant professor in Computer Science at GLA University Mathura.

Rakesh Roshan
Rakesh Roshan received his B.Sc. degree from Ranchi University, MCA from UPTU Lucknow, M.Tech (IT) from Mysore and he is pursuing his Ph.D from MBU, Solan. His area of interest includes artificial intelligence, data bases, and software engineering. He is IBM DB2 and RAD certified professional. Currently he is working as an assistant professor in IT at ITS Ghaziabad, India.

Rabins Porwal
Dr. Rabins Porwal earned his B.Sc. degree from CSJMU Kanpur, M.Sc. and Ph.D from DEI Agra. He is senior fellow of IEEE. He got various awards and scholarships during his academic and research career including JRF, SRF, CSIR fellowship, gold medal in graduation, national scholarship from 10th standard up to graduation etc. He is treasurer of Computer Society of India (Ghaziabad section). He is life member of CSI and The Indian Science Congress Association (ISCA). He is a member of ACM and Indian Society for Technical Education (ISTE). He is currently working as an associate professor in IT at ITS Ghaziabad, India.

Ashish Khare
Dr. Ashish Khare received his B.Sc, M.Sc and Ph.D degrees from University of Allahabad. Dr. Khare has more than 50 research papers in international/national journals and conference proceedings. His research area includes image processing, medical imaging, video processing, soft computing, and algorithm analysis. He is currently employed as an assistant professor at Department of Electronics and Communication, University of Allahabad.


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