Efficient Online Object Tracking Scheme for Challenging Scenarios

Mehmood, Khizer; Ali, Ahmad; Jalil, Abdul; Khan, Baber; Cheema, Khalid Mehmood; Murad, Maria; Milyani, Ahmad H.

doi:10.3390/s21248481

Open AccessArticle

Efficient Online Object Tracking Scheme for Challenging Scenarios

by

Khizer Mehmood

¹

,

Ahmad Ali

²,

Abdul Jalil

¹,

Baber Khan

¹,

Khalid Mehmood Cheema

^3,*,

Maria Murad

¹

and

Ahmad H. Milyani

⁴

¹

Department of Electrical Engineering, International Islamic University, Islamabad 44000, Pakistan

²

Department of Software Engineering, Bahria University, Islamabad 44000, Pakistan

³

School of Electrical Engineering, Southeast University, Nanjing 210096, China

⁴

School of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia

^*

Author to whom correspondence should be addressed.

Sensors 2021, 21(24), 8481; https://doi.org/10.3390/s21248481

Submission received: 4 October 2021 / Revised: 3 December 2021 / Accepted: 14 December 2021 / Published: 20 December 2021

(This article belongs to the Special Issue Sensors for Object Detection, Classification and Tracking)

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Abstract

Visual object tracking (VOT) is a vital part of various domains of computer vision applications such as surveillance, unmanned aerial vehicles (UAV), and medical diagnostics. In recent years, substantial improvement has been made to solve various challenges of VOT techniques such as change of scale, occlusions, motion blur, and illumination variations. This paper proposes a tracking algorithm in a spatiotemporal context (STC) framework. To overcome the limitations of STC based on scale variation, a max-pooling-based scale scheme is incorporated by maximizing over posterior probability. To avert target model from drift, an efficient mechanism is proposed for occlusion handling. Occlusion is detected from average peak to correlation energy (APCE)-based mechanism of response map between consecutive frames. On successful occlusion detection, a fractional-gain Kalman filter is incorporated for handling the occlusion. An additional extension to the model includes APCE criteria to adapt the target model in motion blur and other factors. Extensive evaluation indicates that the proposed algorithm achieves significant results against various tracking methods.

Keywords: object tracking; image processing; fractional-gain Kalman filter; APCE

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MDPI and ACS Style

Mehmood, K.; Ali, A.; Jalil, A.; Khan, B.; Cheema, K.M.; Murad, M.; Milyani, A.H. Efficient Online Object Tracking Scheme for Challenging Scenarios. Sensors 2021, 21, 8481. https://doi.org/10.3390/s21248481

AMA Style

Mehmood K, Ali A, Jalil A, Khan B, Cheema KM, Murad M, Milyani AH. Efficient Online Object Tracking Scheme for Challenging Scenarios. Sensors. 2021; 21(24):8481. https://doi.org/10.3390/s21248481

Chicago/Turabian Style

Mehmood, Khizer, Ahmad Ali, Abdul Jalil, Baber Khan, Khalid Mehmood Cheema, Maria Murad, and Ahmad H. Milyani. 2021. "Efficient Online Object Tracking Scheme for Challenging Scenarios" Sensors 21, no. 24: 8481. https://doi.org/10.3390/s21248481

APA Style

Mehmood, K., Ali, A., Jalil, A., Khan, B., Cheema, K. M., Murad, M., & Milyani, A. H. (2021). Efficient Online Object Tracking Scheme for Challenging Scenarios. Sensors, 21(24), 8481. https://doi.org/10.3390/s21248481

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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