Abstract: For realistically warping one real people image with reference to another template gesture so as to make the stand people jump, hop, or skip, etc., a method of high-fidelity image warping via Killing vector fields（KVF） is proposed, which employs the improved Grab Cut algorithm for object extraction, exploits the semantic skeleton match approach for aligning the skeleton, and makes use of the constrained KVF warping image for jump, hop, or skip, etc. Experiments demonstrate that the presented method could warp the images with less relevance, and high-fidelity warp one stand people with reference to different gesture.