Collision detection is a key step in 3D virtual clothing, and it is difficult to be made real-time using generic collision detection algorithms with relatively high resolution of cloth and human body. This paper exploits depth and normal maps to efficiently detect and resolve collisions between cloth and body. First, body mesh is rendered from prepositioned cameras to generate depth and normal maps. Secondly, the depth of cloth node is computed and then the node is transformed to depth image space. Thirdly, depth is retrieved from the depth map according to the image coordinate of the cloth node and it is compared with the node's depth to determine whether collision happens or not. Lastly, if collision happens, an interpolation parameter is determined by searching the depth image space in the coordinate interval determined by the cloth node positions in previous and current integration step using a modified DDA line rasterization algorithm, and the interpolation parameter is later used to compute the contact point and contact normal which is necessarily for continuous collision response. Experimental results show that the algorithm takes little time in the preprocessing step and is able to provide real-time collision detection and response even when the resolution of cloth mesh and human body is relatively high.