Multi-viewpoint Cameras Research Articles

2P2-E16 多視点カメラシステムを用いたボクセルベース手姿勢推定(VRとインタフェース)

2P2-E16 多視点カメラシステムを用いたボクセルベース手姿勢推定(VRとインタフェース)

A real‐time human movement transfer system for an omnidirectional display

AbstractThis paper proposes a system in which a human image with movement is captured by a multiviewpoint camera and is converted in real time to three‐dimensional data, which are sent by network transfer so that the image can be displayed at a remote site in three dimensions, using an omnidirectional display device. In the proposed system, the target human image is reconstructed in voxelwise, using parallel volume intersection for multiple images. The reconstructed voxels represent only the presence or absence of the object. Then coloring is required, based on texture information that is obtained by projecting the voxel on each image plane. The judgment as to whether the voxel is visible is important in the coloring process. In this study we attempt to achieve real‐time processing from imaging to display. A parallel coloring procedure is developed by using a human image buffer in each camera, so that the visibility of the voxels is judged in real time. In order to investigate the effectiveness of the system, an experimental system for multiviewpoint image processing was constructed using five cameras and six PCs. A human image with movement was captured and a performance of 2.63 FPS was achieved for reconstruction with a spatial resolution of 96×96×96 (a voxel size of 10 mm). The reconstructed data were directly transferred to the omnidirectional display device without being stored in memory, and were displayed, demonstrating the effectiveness of the proposed method. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 90(12): 77–86, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.20416

A hand-pose estimation for vision-based human interfaces

This paper proposes a novel method for a hand-pose estimation that can be used for vision-based human interfaces. The aim of this method is to estimate all joint angles. In this method, the hand regions are extracted from multiple images obtained by a multiviewpoint camera system. By integrating these multiviewpoint silhouette images, a hand pose is reconstructed as a "voxel model." Then, all joint angles are estimated using a three-dimensional model fitting between the hand model and the voxel model. The following two experiments were performed: (1) an estimation of joint angles by the silhouette images from the hand-pose simulator and (2) hand-pose estimation using real hand images. The experimental results indicate the feasibility of the proposed algorithm for vision-based interfaces, although the algorithm requires faster implementation for real-time processing.

Construction of Omni-Directional Images by using Multi-Viewpoint Cameras

Construction of Omni-Directional Images by using Multi-Viewpoint Cameras

A study on resolution and aliasing for multi-viewpoint image acquisition

We equate multi-viewpoint image acquisition with object sampling from different viewpoints, and calculate the resolution of multi-viewpoint camera systems. Aliasing, which occurs with the sampling, leads to depth shifting of objects. For instance, an image of a distant object may be taken as if it were near when aliasing occurs. A condition of the camera pitch free from aliasing is discussed. An appropriate prefilter for the sampling can eliminate alias-causing spatial-frequency components, even when the camera pitch is large. We analyze the characteristics of the prefilters from the aspects of depth shifting, ghosting, and waveform distortion. The experimental results show that a prefilter, which reduces ghosting, can be realized optically. For precise acquisition of multi-viewpoint images, however, a prefilter with electrical processing is needed.