基于三焦距张量及BMA的运动估计和补偿

为克服块匹配位移估计方法 (BMA)不能准确描述物体的旋转、相机镜头的推移 (pan)及缩放的缺点 ,引入计算机视觉中的三线性关系及基于三焦距张量的像素转移进行运动估计和补偿。将像素转移与块匹配运动估计和补偿方法相结合 ,通过实际的图像序列比较了这种方法与单纯 BMA方法的运动补偿效果 ,结果表明 ,在有相机平移及景物有深度变化时 ,本文方法的效果明显优于单纯 BMA方法。

MOTION ESTIMATION AND COMPENSATION BASED ON TRIFOCAL TENSOR AND BMA

To overcome some drawbacks of the block matching algorithm (BMA), which can not accurately describe object rotation, camera panning and zooming, this paper introduces the trilinear constraint and trifocal tensor based pixel transfer used in computer vision for motion estimation and compensation. In this method, the trifocal tensor is first estimated by an algorithm based on projection matrix, corresponding relations between two of three images are then determined by BMA and represented with block based motion vectors, and finally, motion estimation and compensation are carried out by trifocal transferring. As it is not accurate to approximate the dense correspondence between two of the three views by the above block based motion vectors, using trifocal transferring only will not yield good compensation results. To solve this problem, the paper further puts forward a motion estimation method combining trifocal transferring with BMA. Experiments have been carried out on video sequences to compare the performance of this method with that of BMA, and the results show that this method is superior when there are scene depth variation and camera translation.