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Visual object tracking—classical and contemporary approaches

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Abstract

Visual object tracking (VOT) is an important subfield of computer vision. It has widespread application domains, and has been considered as an important part of surveillance and security system. VOA facilitates finding the position of target in image coordinates of video frames.While doing this, VOA also faces many challenges such as noise, clutter, occlusion, rapid change in object appearances, highly maneuvered (complex) object motion, illumination changes. In recent years, VOT has made significant progress due to availability of low-cost high-quality video cameras as well as fast computational resources, and many modern techniques have been proposed to handle the challenges faced by VOT. This article introduces the readers to 1) VOT and its applications in other domains, 2) different issues which arise in it, 3) various classical as well as contemporary approaches for object tracking, 4) evaluation methodologies for VOT, and 5) online resources, i.e., annotated datasets and source code available for various tracking techniques.

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Authors and Affiliations

  1. Department of Computer and Information Sciences, Pakistan Institute of Engineering & Applied Sciences, Islamabad, 44000, Pakistan

    Ahmad Ali, Abdul Jalil & Saima Rathore

  2. State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Jianwei Niu & Xiaoke Zhao

  3. Department of Electrical (Telecom) Engineering, NUST Military College of Signals, Islamabad, 44000, Pakistan

    Javed Ahmed

  4. COMSATS Institute of Information Technology, Lahore, 54000, Pakistan

    Muhammad Aksam Iftikhar

Authors
  1. Ahmad Ali
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  2. Abdul Jalil
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  3. Jianwei Niu
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  4. Xiaoke Zhao
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  5. Saima Rathore
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  6. Javed Ahmed
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  7. Muhammad Aksam Iftikhar
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Correspondence to Jianwei Niu.

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Ahmad Ali received his BS in computer sciences (Hons.) from University of Engineering & Technology (UET), Lahore, Pakistan. He completed his MS in system engineering from Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan. Currently, he is pursuing his PhD from PIEAS. His areas of interest are image processing, computer vision, object tracking, artificial intelligence, and speech processing.

Abdul Jalil received his MS and M.Phil in electronics from Qauid-i-Azam University, Islamabad, Pakistan in 1986 and 2000, respectively. He completed his PhD in image and signal processing from Mohammad Ali Jinnah University, Pakistan in 2006. Then, he remained affiliated with University of Sussex for Post Doctorate of 9 months during 2008–09 period. His research interests are related to machine vision and signal, and image processing.

Jianwei Niu received his PhD in computer science from Beihang University (BUAA), China in 2002. He is a professor in the School of Computer Science and Engineering, BUAA, and an IEEE senior member. He has published more than 100 referred papers, and filed more than 30 patents in mobile and pervasive computing. His current research interests include mobile and pervasive computing, mobile video analysis.

Xiaoke Zhao received his MS in computer science in 2014 from Beihang University, China. He received his BS in 2011 from Guiyang University. He has worked as a research intern at the Nokia Research Center in Beijing. His current research interests include computer vision and pattern recognition.

Saima Rathore received the BS degree in software engineering from Fatima Jinnah Women University, Rawalpindi, Pakistan, in 2006 and the MS degree in computer engineering from the University of Engineering and Technology, Taxila, Pakistan in 2008. She completed her PhD in computer science from Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan in 2015. Currently, she is working as a post-doctoral researcher in Perelman School of Medicine, University of Pennsylvania, USA. Her research interests include medical image analysis, segmentation, classification and evolutionary algorithms.

Javed Ahmed received his BE in electronics engineering from NED University of Engineering & Technology, Karachi, Pakistan in 1994. Then, he received his MS in systems engineering with the 2nd position under the fellowship program from Pakistan Institute of Engineering & Applied Sciences (PIEAS), Islamabad, Pakistan in 1997. He joined National Engineering and Scientific Commission in 1997 and worked in the areas of electronics and signal processing. He received his PhD in electrical (telecom) engineering from National University of Sciences & Technology (NUST), Islamabad, Pakistan in 2008. He obtained the Certificate of Achievement from Computer Vision Lab at University of Central Florida, USA in February 2007 for conducting 8-month outstanding joint research with them. His current research areas are image processing, computer vision, signal processing, and soft computing.

Muhammad Aksam Iftikhar completed his BS in computer engineering from University of Engineering and Technology, Lahore, Pakistan in 2007. He received his MS in computer science from the same university in 2010. He completed his PhD from Pakistan Institute of Engineering and Applied Sciences, Islamabad, Pakistan. His primary research areas include image processing (especially medical image processing and analysis), computer vision, machine learning, and pattern recognition.

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Ali, A., Jalil, A., Niu, J. et al. Visual object tracking—classical and contemporary approaches. Front. Comput. Sci. 10, 167–188 (2016). https://doi.org/10.1007/s11704-015-4246-3

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