Detection of moving human using optimized correlation filters in homogeneous environments

Naeem Akbar; Sara Tehsin; Ahmad Bilal; Saddaf Rubab; Saad Rehman; Rupert Young

doi:10.1117/12.2559578

11 May 2020 Detection of moving human using optimized correlation filters in homogeneous environments

Naeem Akbar, Sara Tehsin, Ahmad Bilal, Saddaf Rubab, Saad Rehman, Rupert Young

Proceedings Volume 11400, Pattern Recognition and Tracking XXXI; 114000P (2020) https://doi.org/10.1117/12.2559578
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

Detection of a moving human is challenging for real-time systems. Misdetection in high alert security areas may lead to heavy losses. This paper presents an optimized approach to avoid this misdetection in sensitive areas. Rotation invariant optimized correlation filters are used for detection of humans. Some pre-processing algorithms such as background subtraction and color space conversion have been linked to the correlation filters to minimize processing time and maximize the accuracy of target detection. The experimental tests of the proposed methodology validate that better accuracy can be achieved if the proposed optimized approach is utilized for moving human detection in real-time systems. In future work, the proposed approach will be extended to detect human activity at night and thermal imagery.

Conference Presentation

Citation Download Citation

Naeem Akbar, Sara Tehsin, Ahmad Bilal, Saddaf Rubab, Saad Rehman, and Rupert Young "Detection of moving human using optimized correlation filters in homogeneous environments", Proc. SPIE 11400, Pattern Recognition and Tracking XXXI, 114000P (11 May 2020); https://doi.org/10.1117/12.2559578

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