Satbir Singh

Work place: Dr.B R Ambedkar National Institute of Technology, Jalandhar, India



Research Interests: Computer Science & Information Technology, Signal Processing, Computer systems and computational processes, Computer Vision, Computer Graphics and Visualization


Satbir Singh Satbir Singh received M.E in Electronics and Communication Engineering from Thapar University, Patiala, India. He is presently working with Central scientific Instruments Organization, Chandigarh, India. Previously, he has a working experience as Senior Scientific Officer with Electronics and Communication Engineering Department of Delhi Technological University, Delhi and as a Project Engineer with Centre of Advanced Computing, Mohali, India. His research interests include signal processing, computer vision and IoT. Currently, he is pursuing Ph.D. from National Institute of Technology, Jalandhar, India.

Author Articles
Object tracking via a Novel Parametric Decisions based RGB-Thermal Fusion

By Satbir Singh Arun Khosla Rajiv Kapoor

DOI:, Pub. Date: 8 Aug. 2023

The thermo- visual fusion based tracking has been deployed for overcoming the shortcomings of alone vision-based object tracking. The assistance from both domains should be wisely merged so that it should result in a useful practice for object tracking. Several techniques had been developed recently to implement a brilliant fusion, but this undeveloped field still inhibits many unsolved challenges. The proposed method aims at increasing the effectiveness of tracking by bi-modal fusion with the introduction of a new set of rules based upon the parameters generated from the decision of individual modality trackers. This practice helps to achieve output by only a single run of the fusion process in every frame. The method also proposes to use minimal information from individual trackers in normal conditions and incorporates the use of supplementary information from imageries merely in case of diverse working conditions. This procedure, in turn, lessens the computations and hence reduces time to process. The experiments performed on well-known publically available datasets show the advantages of the proposed method over the individual visual domain tracking and other existing states of the art fusion techniques.

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Visual Object Tracking by Fusion of Audio Imaging in Template Matching Framework

By Satbir Singh Arun Khosla Rajiv Kapoor

DOI:, Pub. Date: 8 Aug. 2019

Audio imaging can play a fundamental role in computer vision, in particular in automated surveillance, boosting the accuracy of current systems based on standard optical cameras. We present here a method for object tracking application that fuses visual image with an audio image in the template-matching framework. Firstly, an improved template matching based tracking is presented that takes care of the chaotic movements in the template-matching algorithm. Then a fusion scheme is presented that makes use of deviations in the correlation scores pattern obtained across the individual frame in each imaging domain. The method is compared with various state of art trackers that perform track estimation using only visible imagery. Results highlight a significant improvement in the object tracking by the assistance of audio imaging using the proposed method under severe challenging vision conditions such as occlusions, object shape deformations, the presence of clutters and camouflage, etc.

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Object Tracking with a Novel Visual-Thermal Sensor Fusion Method in Template Matching

By Satbir Singh Arun Khosla Rajiv Kapoor

DOI:, Pub. Date: 8 Jul. 2019

Recently there has been an increase in the use of thermal-visible conjunction technique in the field of surveillance applications due to complementary advantages of both. An amalgamation of these for tracking requires a reasonable scientific procedure that can efficiently make decisions with sound accuracy and excellent precision. The proposed research presents a unique idea for obtaining a robust track estimate with the thermo-visual fusion in the context of fundamental template matching. This method firstly introduces a haphazard transporting control mechanism for individual modality tracking that avoids unexpected estimates. Then it brings together an efficient computation procedure for providing the weighted output using minimal information from the individual trackers. Experiments performed on publically available datasets mark the usefulness of the proposed idea in the context of accuracy, precision and process time in comparison with the state of art methods.

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