Moving Object Detection in Complex Scene Using Spatiotemporal Structured-Sparse RPCA

Sajid Javed, Arif Mahmood, Somaya Al-Maadeed, Thierry Bouwmans, Soon Ki Jung

Research output: Contribution to journalArticlepeer-review

94 Scopus citations


Moving object detection is a fundamental step in various computer vision applications. Robust principal component analysis (RPCA)-based methods have often been employed for this task. However, the performance of these methods deteriorates in the presence of dynamic background scenes, camera jitter, camouflaged moving objects, and/or variations in illumination. It is because of an underlying assumption that the elements in the sparse component are mutually independent, and thus the spatiotemporal structure of the moving objects is lost. To address this issue, we propose a spatiotemporal structured sparse RPCA algorithm for moving objects detection, where we impose spatial and temporal regularization on the sparse component in the form of graph Laplacians. Each Laplacian corresponds to a multi-feature graph constructed over superpixels in the input matrix. We enforce the sparse component to act as eigenvectors of the spatial and temporal graph Laplacians while minimizing the RPCA objective function. These constraints incorporate a spatiotemporal subspace structure within the sparse component. Thus, we obtain a novel objective function for separating moving objects in the presence of complex backgrounds. The proposed objective function is solved using a linearized alternating direction method of multipliers based batch optimization. Moreover, we also propose an online optimization algorithm for real-time applications. We evaluated both the batch and online solutions using six publicly available data sets that included most of the aforementioned challenges. Our experiments demonstrated the superior performance of the proposed algorithms compared with the current state-of-the-art methods.

Original languageBritish English
Article number8485415
Pages (from-to)1007-1022
Number of pages16
JournalIEEE Transactions on Image Processing
Issue number2
StatePublished - Feb 2019


  • Background subtraction
  • foreground detection
  • moving objects detection
  • RPCA
  • spatiotemporal regularization


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