视频特技外文翻译(编辑修改稿)

视频特技外文翻译(编辑修改稿)内容摘要：

ble to emphasize motion using traditional animation cues[44] such as streaklines, anticipation and deformation. Their unique contribution is to build a video based NPR system which can process over an extended period of time rather than on a per frame basis. This advance allows them to analyze trajectories, make decisions regarding occlusions and collisions and do motion emphasis. In this work we will also regard video as a whole rather than the sum of individual frames. However, their segmentation in “puter vision ponent” suffers labor intensity, since users have to manually identify polygons, which are “shrink wrapped” to the feature’s edge contour using snake relaxation[72] before tracking. And their tracking is based on the assumption that contour motion may be modeled by a linear conformal affine transform(LCAT) in the image plane. We try to use a more automatic segmentation and nonrigid region tracking to improve the capability of video analysis. See Figure for some examples. Another highlevel videobased NPAR system is provided by Wang et al.[69]. They regard video as a 3D lattice(x,y,t) and then implement spatiotemporal segmentation of homogeneous regions using mean shift[14] or improved mean shift[70] to get volumes of contiguous pixels with similar colour. Users have to define salient regions by manually sketching on keyframes and the system thus automatically generates salient regions per frame. This naturally build the correspondence between successive frames, avoiding nonrigid region tracking. Their rendering is based on mean shift guided interpolation. The rendering style is limited to several approaches, such as changing segment colour and placing strokes and ignores motion analysis and motion emphasis. Our system segments keyframe using 2D mean shift, identifies salient regions and then tracks them over the whole sequence. We extract motion information from the results and then do motion emphasis. See Figure for some examples. Some other NPAR techniques Bregler et la present a technique called “cartoon capture and retargeting” in [7] which is u。