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Precise Object Detection Using Iterative Superpixels Grouping Method

         

摘要

cqvip:The region completeness of object detection is very crucial to video surveillance,such as the pedestrian and vehicle identifications.However,many conventional object detection approaches cannot guarantee the object region completeness because the object detection can be influenced by the illumination variations and clustering backgrounds.In order to overcome this problem,we propose the iterative superpixels grouping(ISPG)method to extract the precise object boundary and generate the object region with high completeness after the object detection.First,by extending the superpixel segmentation method,the proposed ISPG method can improve the inaccurate segmentation problem and guarantee the region completeness on the object regions.Second,the multiresolutionsuperpixel-basedregioncompleteness enhancement method is proposed to extract the object region with high precision and completeness.The simulation results show that the proposed method outperforms the conventional object detection methods in terms of object completeness evaluation.

著录项

  • 来源
    《电子科技学刊:英文版》 |2017年第2期|P.153-160|共8页
  • 作者单位

    [1]Department of Computer Science and infonnation Engineering Chung Hua University;

    Hsinchu 300 [2]Architecture and Building Research lnstitute;

    New Taipci Citv 100;

    [1]Department of Computer Science and infonnation Engineering Chung Hua University;

    Hsinchu 300 [2]Architecture and Building Research lnstitute;

    New Taipci Citv 100;

    [1]Department of Computer Science and infonnation Engineering Chung Hua University;

    Hsinchu 300 [2]Architecture and Building Research lnstitute;

    New Taipci Citv 100;

    [1]Department of Computer Science and infonnation Engineering Chung Hua University;

    Hsinchu 300 [2]Architecture and Building Research lnstitute;

    New Taipci Citv 100;

    [1]Department of Computer Science and infonnation Engineering Chung Hua University;

    Hsinchu 300 [2]Architecture and Building Research lnstitute;

    New Taipci Citv 100;

    [1]Department of Computer Science and infonnation Engineering Chung Hua University;

    Hsinchu 300 [2]Architecture and Building Research lnstitute;

    New Taipci Citv 100;

  • 原文格式 PDF
  • 正文语种 CHI
  • 中图分类 TP391.41;
  • 关键词

    目标检测 迭代处理 分组 目标区域 分割方法 区域提取 视频监控 车辆识别;

    机译:目标检测 迭代处理 分组 目标区域 分割方法 区域提取 视频监控 车辆识别;
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