彭祺, 仲思东, 屠礼芬, 梅天灿. 基于空间位置特征的运动阴影检测方法[J]. 机器人, 2012, 34(5): 614-619. DOI: 10.3724/SP.J.1218.2012.00614
引用本文: 彭祺, 仲思东, 屠礼芬, 梅天灿. 基于空间位置特征的运动阴影检测方法[J]. 机器人, 2012, 34(5): 614-619. DOI: 10.3724/SP.J.1218.2012.00614
PENG Qi, ZHONG Sidong, TU Lifen, MEI Tiancan. Moving Shadow Detection Based on Space Location Feature[J]. ROBOT, 2012, 34(5): 614-619. DOI: 10.3724/SP.J.1218.2012.00614
Citation: PENG Qi, ZHONG Sidong, TU Lifen, MEI Tiancan. Moving Shadow Detection Based on Space Location Feature[J]. ROBOT, 2012, 34(5): 614-619. DOI: 10.3724/SP.J.1218.2012.00614

基于空间位置特征的运动阴影检测方法

Moving Shadow Detection Based on Space Location Feature

  • 摘要: 针对现有依据光学属性检测阴影的方法对不同场景通用性不强、对光照变化敏感等问题, 提出一种基于空间位置特征的运动阴影检测方法. 用经过标定的双目立体摄像机同时采集背景图像像对. 离线获取背景图像对中各匹配点的位置对应关系. 投射阴影附着在背景表面,与背景图像像对的位置对应关系相同, 故可以通过比较前景图像像对各点在背景对应位置上像素值的相似程度来剔除阴影. 该方法不需对环境特征及光照条件等先验知识的学习,各种复杂光照条件均不影响其检测精度. 实验表明,该方法能够有效地检测出运动阴影.

     

    Abstract: In order to overcome the problems of poor universality and sensitivity of light change in the existing shadow detection methods based on optical properties, a moving shadow detection method based on space location feature is introduced. A calibrated binocular stereo camera is used to capture stereo background images at the same time. The position relationships between matching points from the pair of background images is calculated off-line. The cast shadows adhere to the background surface, and the matching points of that shadow have the same position relationships with that of the background stereo images, so the cast shadows can be removed by comparing the level of similarities of pixel values between the left and right images on the position of matching points in the background. Prior knowledge about neither the environment characteristics nor the lighting conditions is required in the proposed approach, and all kinds of complicated lighting conditions will not affect the detection precision. Experimental results demonstrate that this approach can effectively detect moving shadows.

     

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