Intelligent Visual Tracking in Unstabilized Videos

Kamlesh Verma, Debashis Ghosh, Harsh Saxena, Himanshu Singh, Rajeev Marathe and Avnish Kumar
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Kamlesh Verma: IRDE, DRDO, Ministry of Defence, India & Indian Institute of Technology, Roorkee, India
Debashis Ghosh: Indian Institute of Technology, Roorkee, India
Harsh Saxena: MSIT, GGSIP University, Delhi, India
Himanshu Singh: IRDE, DRDO, Ministry of Defence, India
Rajeev Marathe: IRDE, DRDO, Ministry of Defence, India
Avnish Kumar: IRDE, DRDO, Ministry of Defence, India

International Journal of Natural Computing Research (IJNCR), 2020, vol. 9, issue 3, 54-75

Abstract: Visual tracking requirement is increasing day by day due to the availability of high-performance digital cameras at low prices. Visual tracking becomes a complex problem when cameras suffer with unwanted and unintentional motion, resulting in motion-blurred unstabilized video. The problem in hand becomes more challenging when the target of interest is to be detected automatically in this unstabilized video. This paper presents a comprehensive single intelligent solution for these problems. The proposed algorithm auto-detects the camera motion, filters out the unintentional motion while stabilizing the video keeping intentional motion only using speeded-up robust features (SURF) technique. Motion smear due to unstabilization is also removed, providing sharp stabilized video output with video quality enhancement of up to 20dB. Gabor filter is used innovatively for auto-detection of target of interest in each stabilized frame. Then the target is tracked using SURF method.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jncr00:v:9:y:2020:i:3:p:54-75

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