A method for recovery of compact volumetric models for shape representation of single-part objects in computer vision is introduced. The models are superquadrics with parametric deformations (bending, tapering, and cavity deformation). The input for the model recovery is three-dimensional range points. Model recovery is formulated as a least-squares minimization of a cost function for all range points belonging to a single part. During an iterative gradient descent minimization process, all model parameters are adjusted simultaneously, recovery position, orientation, size, and shape of the model, such that most of the given range points lie close to the model's surface. A specific solution among several acceptable solutions, where are all minima in the parameter space, can be reached by constraining the search to a part of the parameter space. The many shallow local minima in the parameter space are avoided as a solution by using a stochastic technique during minimization. Results using real range data show that the recovered models are stable and that the recovery procedure is fast.

We present a novel approach to reliable and efficient recovery of part-descriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g., in terms of surfaces). The approach is based on the recover-and-select paradigm [10]. We present several experiments on real and synthetic range images, where we demonstrate the stability of the results with respect to viewpoint and noise.

Visualizing music in a meaningful and intuitive way is a challenge. Our aim is to visualize music by interconnecting similar aspects in music and in visual perception. We focus on visualizing harmonic relationships between tones and colours. Related existing visualizations map tones or keys into a discrete set of colours. As concurrent (simultaneous) tones are not perceived as entirely separate, but also as a whole, we present a novel method for visualizing a group of concurrent tones (limited to the pitches of the 12-tone chromatic scale) with one colour for the whole group. The basis for calculation of colour is the assignment of key spanning circle of thirds to the colour wheel. The resulting colour is not limited to discrete set of colours: similar tones, chords and keys have similar colour hue; dissonance and consonance are represented by low and high colour saturation respectively. The proposed method is demonstrated as part of our prototype music visualization system using extended 3-dimensional piano roll notation.