A GPU-based implementation of motion detection from a moving platform

Qian Yu, G. Medioni
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引用次数: 40

Abstract

We describe a GPU-based implementation of motion detection from a moving platform. Motion detection from a moving platform is inherently difficult as the moving camera induces 2D motion field in the entire image. A step compensating for camera motion is required prior to estimating of the background model. Due to inevitable registration errors, the background model is estimated according to a sliding window of frames to avoid the case where erroneous registration influences the quality of the detection for the whole sequence. However, this approach involves several characteristics that put a heavy burden on real-time CPU implementation. We exploit GPU to achieve significant acceleration over standard CPU implementations. Our GPU-based implementation can build the background model and detect motion regions at around 18 fps on 320times240 videos that are captured for a moving camera.
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基于gpu的移动平台运动检测实现
我们描述了一个基于gpu的移动平台运动检测的实现。由于移动的摄像机会在整个图像中产生二维运动场,因此从移动平台进行运动检测本身就很困难。在估计背景模型之前,需要对相机运动进行步进补偿。由于不可避免的配准误差,背景模型采用帧间滑动窗口估计,避免配准错误影响整个序列的检测质量。然而,这种方法涉及到的几个特性给实时CPU实现带来了沉重的负担。我们利用GPU实现比标准CPU实现显著的加速。我们基于gpu的实现可以构建背景模型,并在为移动摄像机捕获的320times240视频中以大约18 fps的速度检测运动区域。
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