Motion recognition of lower limb without marks

Tracing motion of lower limb is the basis of analyzing motion of whole body. In this paper, the image sequences are transformed to distance images in which each pixel represent its distance to the background. The process is as follows: we first get the binary image sequences from the original image sequences by threshold selection, and we extract interesting region that is the part of the leg. Pixel value within lower limb is represent as '1' and pixel within background as '0'. Then scanning each binary image from top to bottom. As we are scanning one binary image, we compare every pixel value within the object with its neighbors to get new value. If the binary image is denoted by f(i,j) where (i,j) is coordinate of the pixel and f(i,j) is the pixel value, we scan the image forward, and the pixel's new value denoted by g(i,j) is as follows: g(i,j) equals 0, if f(i,j) equals 0 g(i,j) equals min [g(i-1,j)+1, g(i,j-1)+1], if f(i,j) equals 1 Then we scan the g (i,j) from bottom to top. As we are scanning, we compare every pixel value within the object with its neighbors to get new value denoted by h(i,j): h(i,j) equals min [g(i,j), h(i-1,j)+1, h(i,j-1)+1]. We denote h (i,j) as the distance image of the original image f (i,j). h (i,j) is pixel' minimum distance to the background. The distance image sequences can reflect geometric characters of images very well. The paper proposes a correlation matching method on distance images, and give matching result of four joints on the leg. The result shows that this is an effective method.