Abstract We present a technique for creating a smoothly varying sequence of procedural textures that interpolates between arbitrary input samples of texture. This texture transformation uses a library of procedural shaders and selects the correct shaders and associated parameters to accomplish the task. In general, selecting a procedural texture from a library, or finding the correct parameters to produce a smooth texture transition can be complex and time consuming. We propose a strategy for automating this process. While superficially this problem appears intractable for both humans and computational systems, its natural characteristics make a computational solution feasible. We present an algorithm and experimental results demonstrating this approach. Transformation between two textures can then be achieved procedurally, while enforcing perceptual similarity constraints between adjacent texture frames. We describe a technique for efficiently sampling the parameter domain of a shader based on a texture similarity function to create a smooth path through its texture range. In the case of evolving between several shaders, a method is described to obtain the best jump‐points which can be used to connect different shaders smoothly in texture space. Several examples of the technique are shown, and future directions as well as potential problems are discussed. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Texture

This paper describes an approach to the automated creation of virtual realities (or virtual maps) of an a priori unknown environment by using a mobile robot. The method we propose is aimed at the creation of an image-based or iconic map, rather than a representation in terms of 2D or 3D spatial occupancy. A key aspect of this is having a mobile robot automatically select points and views of interest that can be used to exemplify the appearance of the environment. This paper develops the use of alpha-backtracking as a technique to efficiency select these points of estimated globally maximum interest.

This paper describes the fully automatic creation of an environment's description using an image-based representation. This representation is a collection of cylindrical sample images combined into an "image-based virtual reality". The locations at which the environment will be sampled are chosen automatically using an operator inspired by models of human visual attention and saccadic motion. The image acquisition is performed by a mobile robot. The selection of vantage points is based on an analysis of the edge structure of sampled panoramic images. In order to trade off the optimality of the generated description of the navigation effort required in solving the online problem, a concept referred to as alpha-backtracking is introduced. The paper illustrates sample data acquired by the procedure.

Describes an integrated system for the automatic construction of image-based virtual realities to describe a real environment. A mobile robot autonomously navigates through the environment and uses a camera to make observations. At locations that are deemed sufficiently interesting, panoramic images are collected that are used to construct a multi-node VR movie. Images of the environment are classified in terms of two features related to human attention: edge element density and edge orientation. The system deems locations interesting if they are sufficiently different from the surrounding environment. The parameterization of the surrounding environment is computed either in a pre-computation pass, or online using a technique termed alpha-backtracking. The panoramic images that describe the environment are automatically joined together in a navigable movie that simulates motion in the real environment.