Hybrid object detection using improved three frame differencing and background subtraction

N. Srivastav, S. Agrwal, S. Gupta, Saurabh R. Srivastava, Blessy Chacko, Hema Sharma
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引用次数: 24

Abstract

Object Detection and Tracking in video has applied in robotics, video-surveillance; human-computer interaction etc. and different approach of object detection e.g. Background subtraction, frame differencing. Motion based recognition is one of the methods to detect objects in sequence of image. In this method, a video sequence containing a large number of images is used to extract motion information. Two frame differencing is very easy but there is problem of holes. Three frame differencing and background subtraction have solved the problem of holes of two frames till a limit. Background subtraction is used for stable background video but Dynamic Background subtraction is capable to detect object in video with gradual background changes. So there is scope of work such that holes problem should be reduced more and object should be detected better in dynamic changes in background. In this paper, the proposed technique is able to reduce the holes problem in dynamic background updating video.
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采用改进的三帧差分和背景减法的混合目标检测
视频中的目标检测与跟踪已应用于机器人、视频监控等领域;人机交互等以及不同的目标检测方法,如背景减法、帧差。基于运动的识别是在图像序列中检测物体的方法之一。该方法利用包含大量图像的视频序列提取运动信息。两帧差是很容易的,但有孔的问题。三帧差分和背景减法在一定程度上解决了两帧的孔洞问题。背景减法用于稳定的背景视频,而动态背景减法能够检测背景逐渐变化的视频中的目标。因此,在动态变化的背景下,需要进一步减少孔洞问题,更好地检测出目标。本文提出的方法能够有效地解决动态背景更新视频中的孔洞问题。
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