{"ID":2890039,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.19730","arxiv_id":"2507.19730","title":"Quaternion-Based Robust PCA for Efficient Moving Target Detection and Background Recovery in Color Videos","abstract":"Moving target detection is a challenging computer vision task aimed at generating accurate segmentation maps in diverse in-the-wild color videos captured by static cameras. If backgrounds and targets can be simultaneously extracted and recombined, such synthetic data can significantly enrich annotated in-the-wild datasets and enhance the generalization ability of deep models. Quaternion-based RPCA (QRPCA) is a promising unsupervised paradigm for color image processing. However, in color video processing, Quaternion Singular Value Decomposition (QSVD) incurs high computational costs, and rank-1 quaternion matrix fails to yield rank-1 color channels. In this paper, we reduce the computational complexity of QSVD to o(1) by utilizing a quaternion Riemannian manifold. Furthermor, we propose the universal QRPCA (uQRPCA) framework, which achieves a balance in simultaneously segmenting targets and recovering backgrounds from color videos. Moreover, we expand to uQRPCA+ by introducing the Color Rank-1 Batch (CR1B) method to further process and obtain the ideal low-rank background across color channels. Experiments demonstrate our uQRPCA+ achieves State Of The Art (SOTA) performance on moving target detection and background recovery tasks compared to existing open-source methods. Our implementation is publicly available on GitHub at https://github.com/Ruchtech/uQRPCA","short_abstract":"Moving target detection is a challenging computer vision task aimed at generating accurate segmentation maps in diverse in-the-wild color videos captured by static cameras. If backgrounds and targets can be simultaneously extracted and recombined, such synthetic data can significantly enrich annotated in-the-wild datas...","url_abs":"https://arxiv.org/abs/2507.19730","url_pdf":"https://arxiv.org/pdf/2507.19730v1","authors":"[\"Liyang Wang\",\"Shiqian Wu\",\"Shun Fang\",\"Qile Zhu\",\"Jiaxin Wu\",\"Sos Again\"]","published":"2025-07-26T01:05:03Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.AI\"]","methods":"[]","has_code":false,"code_links":[{"ID":611730,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2890039,"paper_url":"https://arxiv.org/abs/2507.19730","paper_title":"Quaternion-Based Robust PCA for Efficient Moving Target Detection and Background Recovery in Color Videos","repo_url":"https://github.com/Ruchtech/uQRPCA","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}