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Superpixels-Guided Background Modeling Approach for Foreground Detection

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Recent Innovations in Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 832))

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Abstract

Foreground detection is one of the active research topics in computer vision and a precondition for intelligent video analytics. Background subtraction is often considered as a reliable method for extracting foreground from the video sequences. The real-world challenges such as intermittent object motion, dynamic backgrounds, bad weather conditions, shadows, and illumination variations affect the performance of foreground detection. Most of the conventional background subtraction methods result in faulty detection and fragmented foreground in case of complex scenes. In recent years, deep neural networks make revolutionary advances in the area of foreground detection. The convolutional neural networks based background subtraction methods are notable for their performance but their performance drop in case of unseen videos and incur high-computational cost. In this paper, we investigate the fusion of superpixel with an adaptive background modeling for foreground detection in several challenging videos. A non-iterative clustering method is adopted for superpixel clustering because of its computational efficiency. Integration of effective superpixel algorithm with background subtraction has paved the way for improvements in unsupervised background subtraction methods. The proposed method is evaluated on different videos of changedetection.net 2014 dataset in order to validate its effectiveness on critical challenges of background subtraction.

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Author information

Authors and Affiliations

  1. Shri Mata Vaishno Devi University, Katra, J&K, India

    Rudrika Kalsotra & Sakshi Arora

Authors
  1. Rudrika Kalsotra
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  2. Sakshi Arora
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Editor information

Editors and Affiliations

  1. KIET Group of Institutions, Ghaziabad, India

    Pradeep Kumar Singh

  2. Department of CSE, Central University of Jammu, Jammu and Kashmir, India

    Yashwant Singh

  3. Department of Electrical Engineering, IIT Patna, Patna, India

    Maheshkumar H. Kolekar

  4. Department of Management Studies and School of Artificial Intelligence, Indian Institute of Technology Delhi, New Delhi, Delhi, India

    Arpan Kumar Kar

  5. School of Technology, Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal

    Paulo J. S. Gonçalves

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Kalsotra, R., Arora, S. (2022). Superpixels-Guided Background Modeling Approach for Foreground Detection. In: Singh, P.K., Singh, Y., Kolekar, M.H., Kar, A.K., Gonçalves, P.J.S. (eds) Recent Innovations in Computing. Lecture Notes in Electrical Engineering, vol 832. Springer, Singapore. https://doi.org/10.1007/978-981-16-8248-3_25

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