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We present a method for animating 3D models of animals from existing live video sequences such as wild life documentaries. Videos are first segmented into binary images on which Principal Component Analysis (PCA) is applied. The time-varying coordinates of the images in the PCA space are then used to generate 3D animation. This is done through interpolation with Radial Basis Functions (RBF) of 3D pose examples associated with a small set of key-images extracted from the video. In addition to this processing pipeline, our main contributions are: an automatic method for selecting the best set of key-images for which the designer will need to provide 3D pose examples. This method saves user time and effort since there is no more need for manual selection within the video and then trials and errors in the choice of key-images and 3D pose e...

Current approaches to skeleton generation are based on topological and geometrical information only; this can be insufficient for realistic character animation, since the location of the joints does not usually match the real bone structure of the model. This paper proposes the use of anatomical information to enhance the skeleton. Using a harmonic function, this information can be recovered from the skeleton itself, which is guaranteed not to have undesired endpoints. The skeleton is computed as a Reeb graph of such a function over the surface of the model. Starting from one point selected on the head of the character, the entire process is fast, automatic and robust; it generates skeletons whose joints can be associated with the character's anatomy. Results are provided, including a quantitative validation of the generated skeletons.

Skeletons are at the core of 3D character animation. The goal of this work is to design a morphable model of 3D skeleton for four footed animals, controlled by a few intuitive parameters. This model enables the automatic generation of an animation skeleton, ready for character rigging, from a few simple measurements performed on the mesh of the quadruped to animate. Quadruped animals - usually mammals - share similar anatomical structures, but only a skilled animator can easily translate them into a simple skeleton convenient for animation. Our approach for constructing the morphable model thus builds on the statistical learning of reference skeletons designed by an expert animator. This raises the problems of coping with data that includes both translations and rotations, and of avoiding the accumulation of errors due to its hierarchi...

We present a method for animating 3D models of animals from existing live video sequences such as wild life documentaries. Videos are first segmented into binary images on which Principal Component Analysis (PCA) is applied. The time-varying coordinates of the images in the PCA space are then used to generate 3D animation. This is done through interpolation with Radial Basis Functions (RBF) of 3D pose examples associated with a small set of key-images extracted from the video. In addition to this processing pipeline, our main contributions are: an automatic method for selecting the best set of key-images for which the designer will need to provide 3D pose examples. This method saves user time and effort since there is no more need for manual selection within the video and then trials and errors in the choice of key-images and 3D pose e...

We present a method for animating 3D models of animals from existing live video sequences such as wild life documentaries. Videos are first segmented into binary images on which principal component analysis (PCA) is applied. The time-varying coordinates of the images in the PCA space are then used to generate 3D animation. This is done through interpolation with radial basis functions of 3D pose examples associated with a small set of keyimages extracted from the video. In addition to this processing pipeline, our main contributions are: an automatic method for selecting the best set of key-images for which the designer will need to provide 3D pose examples, and a simple algorithm based on PCA images to resolve 3D pose prediction ambiguities. These ambiguities are inherent to many animal gaits when only monocular view is available.