{
  "id": "1109.0882",
  "version": "v2",
  "published": "2011-09-05T13:08:24.000Z",
  "updated": "2012-06-23T00:07:06.000Z",
  "title": "Moving Object Detection by Detecting Contiguous Outliers in the Low-Rank Representation",
  "authors": [
    "Xiaowei Zhou",
    "Can Yang",
    "Weichuan Yu"
  ],
  "comment": "30 pages",
  "categories": [
    "cs.CV"
  ],
  "abstract": "Object detection is a fundamental step for automated video analysis in many vision applications. Object detection in a video is usually performed by object detectors or background subtraction techniques. Often, an object detector requires manually labeled examples to train a binary classifier, while background subtraction needs a training sequence that contains no objects to build a background model. To automate the analysis, object detection without a separate training phase becomes a critical task. People have tried to tackle this task by using motion information. But existing motion-based methods are usually limited when coping with complex scenarios such as nonrigid motion and dynamic background. In this paper, we show that above challenges can be addressed in a unified framework named DEtecting Contiguous Outliers in the LOw-rank Representation (DECOLOR). This formulation integrates object detection and background learning into a single process of optimization, which can be solved by an alternating algorithm efficiently. We explain the relations between DECOLOR and other sparsity-based methods. Experiments on both simulated data and real sequences demonstrate that DECOLOR outperforms the state-of-the-art approaches and it can work effectively on a wide range of complex scenarios.",
  "revisions": [
    {
      "version": "v2",
      "updated": "2012-06-23T00:07:06.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "moving object detection",
      "low-rank representation",
      "named detecting contiguous outliers",
      "object detector",
      "complex scenarios"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 30,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2011arXiv1109.0882Z"
    }
  }
}