Learn More
In this study, we propose a novel framework for constructing a content-based human motion retrieval system. Two major components, including indexing and matching, are discussed and their corresponding algorithms are presented. In indexing, we introduce an affine invariant posture feature and propose an index map structure based on the posture distribution(More)
In this study, we propose a fuzzy logic CBIR (content-based image retrieval) system for finding textures. In our CBIR system, a user can submit textual descriptions and/or visual examples to find the desired textures. After the initial search, the user can give relevant and/or irrelevant examples to refine the query and improve the retrieval efficiency.(More)
In this correspondence, a new approach to retrieving images from a color image database is proposed. Each image in the database is represented by a two-dimensional pseudo-hidden Markov model (2-D PHMM), which characterizes the chromatic and spatial information about the image. In addition, a flexible pictorial querying method is used, by which users can(More)
Human spontaneous motions such as walking and runing are seldom described in detail. However, some well designed motions such as conditioning and rehabilitation exercises are usually described in detail and edited into exercise manuals for training purpose. This paper presents a novel framework for synthesizing new motions based on given motion manuals and(More)