电子与信息学报
電子與信息學報
전자여신식학보
JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY
2013年
8期
1914-1920
,共7页
运动目标检测%相机抖动%角点提取%特征点匹配%背景偏移估计
運動目標檢測%相機抖動%角點提取%特徵點匹配%揹景偏移估計
운동목표검측%상궤두동%각점제취%특정점필배%배경편이고계
Moving object detection%Camera jittering%Corner detection%Feature points matching%Background offset estimation
针对自然环境下运动目标检测时相机抖动问题,该文提出一种背景自适应方案。首先用 Harris 算子检测背景帧和当前帧感兴趣区域的角点,并在小范围内采用相关法和松弛法获取若干稳定的匹配点对。然后通过匹配点对的偏移量来估计相机的抖动参数,恢复出与当前帧匹配的背景帧。最后使用基于多分辨率金字塔模型的背景差分算法来检测运动目标,去除环境中的动态背景噪声和图像模糊引入的较小的相机偏移量估计误差。用公共测试图像的相机抖动序列对该算法进行了验证,并与当前较为先进的算法定性和定量地进行了比较,实验结果表明,该算法可以有效地解决自然环境下相机抖动问题,检测效果评价参数优于当前的算法。
針對自然環境下運動目標檢測時相機抖動問題,該文提齣一種揹景自適應方案。首先用 Harris 算子檢測揹景幀和噹前幀感興趣區域的角點,併在小範圍內採用相關法和鬆弛法穫取若榦穩定的匹配點對。然後通過匹配點對的偏移量來估計相機的抖動參數,恢複齣與噹前幀匹配的揹景幀。最後使用基于多分辨率金字塔模型的揹景差分算法來檢測運動目標,去除環境中的動態揹景譟聲和圖像模糊引入的較小的相機偏移量估計誤差。用公共測試圖像的相機抖動序列對該算法進行瞭驗證,併與噹前較為先進的算法定性和定量地進行瞭比較,實驗結果錶明,該算法可以有效地解決自然環境下相機抖動問題,檢測效果評價參數優于噹前的算法。
침대자연배경하운동목표검측시상궤두동문제,해문제출일충배경자괄응방안。수선용 Harris 산자검측배경정화당전정감흥취구역적각점,병재소범위내채용상관법화송이법획취약간은정적필배점대。연후통과필배점대적편이량래고계상궤적두동삼수,회복출여당전정필배적배경정。최후사용기우다분변솔금자탑모형적배경차분산법래검측운동목표,거제배경중적동태배경조성화도상모호인입적교소적상궤편이량고계오차。용공공측시도상적상궤두동서렬대해산법진행료험증,병여당전교위선진적산법정성화정량지진행료비교,실험결과표명,해산법가이유효지해결자연배경하상궤두동문제,검측효과평개삼수우우당전적산법。
According to the problem of camera jittering under natural environments when detecting moving objects, a background adaptive scheme is proposed in the paper. First, the Harris operator is used to detect corners in the region-of-interest for background and foreground image respectively. A correlation and relaxation method is also applied to a small region to obtain several stable matched points. Then, the camera jitter parameter is estimated with offsets of these matched points and used to recover background image to match against the current image. At last, background difference algorithm based on the multi-resolution pyramid is adopted to detect moving object. It can remove the environment dynamic background noises and some small offset estimation errors caused by image blurring. The proposed algorithm is verified with camera jittering sequence of the public test image and compared with several state-of-the-art algorithms qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm can solve the problem of camera jittering in natural environment effectively. The detected effect evaluation parameter is better than the current algorithms.