Motion tracking system in video based on extensive feature set

Abstract In recent years, object detection and tracking has been a dynamic research area. Rapid development of the multimedia and the associated technologies urge the processing of a huge database of video clips. The processing efficiency lies on the search methodologies utilised in the video processing system. Usage of unsuitable search methodologies may make the processing system ineffective. Hence, effective object detection and tracking system is an essential criterion for searching relevant videos from a huge collection of videos. This paper proposes a unique object detection and tracking system where video segmentation, feature extraction, object detection and tracking are combined perfectly using various features. Initially, the database video clips are segmented into different shots before performing the feature extraction process. The proposed system consists of two stages, namely, feature extraction and tracking of object in the video clips. In the feature extraction stage, firstly, colour feature is extracted based on colour quantisation. Next, edge density feature is extracted for the objects present in the query video. Then, the texture feature is extracted based on LGXP technique. Finally, based on these feature extracted, the object will be detected and the detected objects will be tracked by utilising both forward and backward tracking technique. The proposed methodology proved to be more effective and accurate in object detection and tracking.

[1]  Sherin M. Youssef,et al.  Detection and tracking of multiple moving objects with occlusion in smart video surveillance systems , 2010, 2010 5th IEEE International Conference Intelligent Systems.

[2]  E. Trucco,et al.  Video Tracking: A Concise Survey , 2006, IEEE Journal of Oceanic Engineering.

[3]  Roman Ilin,et al.  Simultaneous detection and tracking of multiple objects in noisy and cluttered environment using maximum likelihood estimation framework , 2010, OCEANS'10 IEEE SYDNEY.

[4]  Cedric Nishan Canagarajah,et al.  Object based video retrieval with local region tracking , 2007, Signal Process. Image Commun..

[5]  Liu Dong,et al.  Monocular-vision-based study on moving object detection and tracking , 2010, 4th International Conference on New Trends in Information Science and Service Science.

[6]  Takashi Toriu,et al.  A Probability-based Model for Detecting Abandoned Objects in Video Surveillance Systems , 2012 .

[7]  Hang Joon Kim,et al.  Object extraction and tracking using genetic algorithms , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[8]  Pinit Kumhom,et al.  Robust ambiguous target handling for visual object tracking , 2010 .

[9]  Daw-Tung Lin,et al.  Real-time automatic recognition of omnidirectional multiple barcodes and DSP implementation , 2010, Machine Vision and Applications.

[10]  Kalpesh R Jadav,et al.  Vision based moving object detection and tracking 1 , 2011 .

[11]  Tieniu Tan,et al.  A real-time object detecting and tracking system for outdoor night surveillance , 2008, Pattern Recognit..

[12]  Brajesh Patel,et al.  Motion Detection based on multi frame video under Surveillance System , 2012 .

[13]  Wei Li,et al.  Scalable continuous object detection and tracking in sensor networks , 2010, J. Parallel Distributed Comput..

[14]  Rama Chellappa,et al.  Online Empirical Evaluation of Tracking Algorithms , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  S. Maltsev,et al.  Minimax Criterion of Similarity for Video Information Processing , 2007, 2007 Siberian Conference on Control and Communications.

[16]  Shih-Chia Huang,et al.  An Advanced Motion Detection Algorithm With Video Quality Analysis for Video Surveillance Systems , 2011, IEEE Transactions on Circuits and Systems for Video Technology.

[17]  Véronique Berge-Cherfaoui,et al.  An embedded multi-modal system for object localization and tracking , 2012, IEEE Intelligent Transportation Systems Magazine.

[18]  Pengfei Zhu,et al.  Video shot segmentation using graph-based dominant-set clustering , 2009, ICIMCS '09.

[19]  Yury Vizilter,et al.  SPECTRUM-BASED OBJECT DETECTION AND TRACKING TECHNIQUE FOR DIGITAL VIDEO SURVEILLANCE , 2012 .

[20]  Edward J. Delp,et al.  Efficient and Low-Complexity Surveillance Video Compression Using Backward-Channel Aware Wyner-Ziv Video Coding , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[21]  Gérard G. Medioni,et al.  Efficient detection and tracking of moving objects in geo-coordinates , 2010, Machine Vision and Applications.

[22]  Véronique Berge-Cherfaoui,et al.  An embedded multi-modal system for object localization and tracking , 2012, 2010 IEEE Intelligent Vehicles Symposium.

[23]  T. Poggio,et al.  A Contour-Based Moving Object Detection and Tracking , 2005, 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance.

[24]  Jie Chen,et al.  Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition , 2010, IEEE Transactions on Image Processing.

[25]  Carlo S. Regazzoni,et al.  A distributed surveillance system for detection of abandoned objects in unmanned railway environments , 2000, IEEE Trans. Veh. Technol..

[26]  D. Manjula.  Adaptive Background subtraction in Dynamic Environments Using Fuzzy Logic , 2010 .

[27]  Dmitry B. Goldgof,et al.  Performance Evaluation of Object Detection and Tracking in Video , 2006, ACCV.

[28]  Chandrika Kamath,et al.  Salient points for tracking moving objects in video , 2005, IS&T/SPIE Electronic Imaging.

[29]  Cheng Wang,et al.  Independently moving object detection and tracking using stereo vision , 2010, The 2010 IEEE International Conference on Information and Automation.

[30]  Narciso García,et al.  An efficient multiple object detection and tracking framework for automatic counting and video surveillance applications , 2012, IEEE Transactions on Consumer Electronics.

[31]  Vasile Gui,et al.  A fast algorithm for background tracking in video surveillance, using nonparametric kernel density estimation , 2005 .

[32]  Liang Xiao,et al.  Research on moving object detection and tracking , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[33]  Chi-Man Pun,et al.  Fast and Robust Color Feature Extraction for Content-based Image Retrieval , 2011 .

[34]  Rogério Schmidt Feris,et al.  Robust Detection of Abandoned and Removed Objects in Complex Surveillance Videos , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[36]  Nihat Yilmaz,et al.  A real-time object tracking by using fuzzy controller for vision-based mobile robot , 2011 .