In this paper, an energy-collection-based non-coherent IR-UWB receiver allowing low complexity and low power consumption is proposed for short range data communication. The proposed receiver consists of an on-the-fly integrator, a 1-bit digital sampler, a pre-processor and a digital symbol synchronizer. The on-the-fly integrator for energy collection and the 1-bit digital sampler reduce complexity of IR-UWB system. Furthermore, with a simple digital filter in the pre-processing unit, SNR and robustness of the receiver against time-varying channel are enhanced. Also the receiver complexity is diminished by a simple scheme of symbol synchronization based on rough time information about incoming pulses, not requiring exact timing information. The performance of the proposed receiver is simulated based on IEEE 802.15.4a channel model and the algorithms are implemented and verified on a FPGA.

Construction of large-scale virtual environment is gaining more attentions for its applications in virtual mall, virtual sightseeing, tele-presence, etc. This paper presents a framework for building a realistic virtual environment from geometry-based approach. We propose an algorithm to construct a realistic 3-D model from multi-view range data and multi-view texture images. The proposed method tries to adopt the result of region segmentation of range images in some phases of the modeling process. It is shown that the relations obtained from region segmentation are quite effective in improving the result of registration as well as mesh merging.

In this paper, we describe a novel technique to extract a polyhedral description from panoramic range data of a scene taken by a panoramic laser range finder. First, we introduce a reasonable noise model of the range data acquired with a laser radar range finder, and derive a simple and efficient approximate solution of the optimal fitting of a local plane in the range data under the assumed noise model. Then, we compute the local surface normals using the proposed method and extract stable planar regions from the range data by using both the distribution information of local surface normals and their spatial information in the range image. Finally, we describe a method which builds a polyhedral description of the scene using the extracted stable planar regions of the panoramic range data with 360 field of view in a polar coordinate system. Experimental results on complex real range data show the effectiveness of the proposed method.

In this paper, we propose a probabilistic approach to derive an approximate polyhedral description from range data. We first compare several least-squares-based methods for estimation of local normal vectors and select the most robust one based on a reasonable noise model of the range data. Second, we extract the stable planar regions from the range data by examining the distributions of the local normal vectors together with their spatial information in the 2D range image. Instead of segmenting the range data completely, we use only the geometries of the extracted stable planar regions to derive a polyhedral description of the range data. The curved surfaces in the range data are approximated by their extracted plane patches. With a probabilistic approach, the proposed method can be expected to be robust against the noise. Experimental results on real range data from different sources show the effectiveness of the proposed method.

Surface reconstruction and visualization from sparse and incomplete surface data is a fundamental problem and has received growing attention in both computer vision and graphics. This paper presents a computational scheme for realistic visualization of free-formed surfaces from 3D range images. The novelty of this scheme is that by integrating computer vision and computer graphics techniques, we dynamically construct a mesh representation of the arbitrary view of the surfaces, from a view-invariant shape description obtained from 3D range images. We outline the principle of this scheme and describle the frame work of a graphical reconstruction model, we call arbitrarily oriented meshes', which is developed based on differential geometry. The experimental results on real range data of human faces are shown.

This paper describes a method for describing a three-dimensional (3-D) scene by integrating color and range data. Range data is obtained by a feature-based stereo method developed in our laboratory. A color image is segmented into uniform color regions. A plane is fitted to the range data inside a segmented region. Regions are classified into three types based on the range data. A certain types of regions are merged and the others remain unless the region type is modified. The region type is modified if the range data on a plane are selected by removing of the some range data. As a result, the scene is represented by planar surfaces with homogeneous colors. Experimental results for real scenes are shown.