Browsing by Author "Tsai, Yu-Pao"

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A flexible display by integrating a wall-size display and steerable projectors
(2006)
Chan, Li-Wei
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Ye, Wei-Shian
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Liao, Shou-Chun
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Tsai, Yu-Pao
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Hsu, Jane
Many wall-size display systems are built to provide large-scale visualization. These systems may be quite successful for some limited applications, but are very inflexible, since these systems only have fixed display regions. This paper integrates steerable projectors whose beam can be moved under computer control onto a wall-size display system to strengthen its display ability. With the steerable projectors, the integrated display system, named Flexible Display, provide an extendable display region. This consists of a large-scale display region and several movable display regions, such that the integrated display system has great potential in the area of human-computer interaction and information visualization. This paper applies the Flexible Display to a virtual museum application to give the users fluent navigation experience. For the application, the Flexible Display provides the following functions: 1) intensity and resolution enhancement of sub-region of display wall, 2) information augmentation, and 3) "stepping user interfaces" for its viewers interacting with display wall.
A new image segmentation method for removing background of object movies by learning shape priors
(2006)
Ko, Cheng-Hung
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Tsai, Yu-Pao
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Shih, Zen-Chung
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Hung, Yi-Ping
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資訊工程學系
This paper proposes a new object movie (OM) segmentation method that incorporates shape priors into the segmentation algorithm. ne shape prior introduced into every image of the OM is learned from the 3D model reconstructed by the volumetric graph cuts. Here, the constraint derived from the discrete medial axis is used to improve the reconstruction algorithm. Our segmentation method requires only a small amount of user intervention, which is to select a subset of acceptable segmentations of the OM after the initial segmentation process. Compared to other techniques, our method provides not only the better segmentation result but also the better 3D reconstruction result.
Automatic geometric and photometric calibration for tiling multiple projectors with a pan-tilt-zoom camera
(2006)
Tsai, Yu-Pao
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Wu, Yen-Nien
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Liao, Shou-Chun
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Shih, Zen-Chung
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Hung, Yi-Ping
Research on creating a large, high-resolution, low-cost display system has become increasingly important due to the growing desire in many fields for bigger and better displays. The goal of this research is to build a seamless large-scale display system by tiling multiple projectors with the help of a pan-tilt-zoom camera. In order to achieve this goal, we took two tasks into consideration: geometric calibration and photometric calibration. Compared to the previous work, our method for geometric calibration is more accurate, thanks to the much higher resolution images acquired by combining several zoom-in images and doing lens correction for the camera at first. For photometric calibration, we achieve color uniformity among projectors by utilizing the same PTZ camera, which is calibrated once with a colorimeter in a factory. Furthermore, we adopted the technique of producing a high dynamic range image from several images of different exposures to increase the measurement accuracy of the camera. In our experiments, the average error of photometric measurement achieved by our method is less than the mean perceptibility tolerance. Our method has great potential for many applications that require large and high-resolution displays.
Background removal of multiview images by learning shape priors
(2007-10-01)
Tsai, Yu-Pao
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Ko, Cheng-Hung
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Hung, Yi-Ping
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Shih, Zen-Chung
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資訊工程學系
Image-based rendering has been successfully used to display 3-D objects for many applications. A well-known example is the object movie, which is an image-based 3-D object composed of a collection of 2-D images taken from many different viewpoints of a 3-D object. In order to integrate image-based 3-D objects into a chosen scene (e.g., a panorama), one has to meet a hard challenge-to efficiently and effectively remove the background from the foreground object. This problem is referred to as multiview images (MVIs) segmentation. Another task requires MVI segmentation is image-based 3-D reconstruction using multiview images. In this paper, we propose a new method for segmenting MVI, which integrates some useful algorithms, including the well-known graph-cut image segmentation and volumetric graph-cut. The main idea is to incorporate the shape prior into the image segmentation process. The shape prior introduced into every image of the MVI is extracted from the 3-D model reconstructed by using the volumetric graph cuts algorithm. Here, the constraint obtained from the discrete medial axis is adopted to improve the reconstruction algorithm. The proposed MVI segmentation process requires only a small amount of user intervention, which is to select a subset of acceptable segmentations of the MVI after the initial segmentation process. According to our experiments, the proposed method can provide not only good MVI segmentation, but also provide acceptable 3-D reconstructed models for certain less-demanding applications.
Generation of binocular object movies from monocular object movies
(2007-01-01)
Chen, Ying-Ruei
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Lo, Wan-Yen
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Tsai, Yu-Pao
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Hung, Yi-Ping
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資訊工程學系
Object movie (OM) is a popular technique for producing interactive 3D artifacts because of its simplicity in production and it photo-realistic ability to present the artifacts, At the same time, many stereoscopic vision techniques are developed for a variety of applications. However, the traditional approach for generating binocular object movies require duplicate effort compared with monocular ones both in the process of acquisition and image processing. Therefore, we propose a framework to generate stereo OMs from monocular ones with the help of an automatically constructed 3D model from the monocular OM. Here, a new representation of the 3D model, named billboard clusters, is proposed for efficient generating binocular views. In order to obtain better results, a novel approach to extract view-independent texture is developed in this work. Besides, billboard clusters can be used to compress the storage capacity of OMs, and to perform relighting so that the binocular OMs can be well augmented into virtual environments with different lighting conditions. This paper describes the methods in detail and reports on its wide applications.