Browsing by Author "Hung, Yi-Ping"

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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.
AR-Arm: Augmented Visualization for Guiding Arm Movement in the First-Person Perspective
(2016)
Han, Ping-Hsuan
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Chen, Kuan-Wen
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Hsieh, Chen-Hsin
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Huang, Yu-Jie
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Hung, Yi-Ping
In many activities, such as martial arts, physical exercise, and physiotherapy, the users are asked to perform a sequence of body movements with highly accurate arm positions. Sometimes, the movements are too complicated for users to learn, even by imitating the action of the coach directly. This paper presents a fully immersive augmented reality (AR) system, which provides egocentric hints to guide the arm movement of the user via a video see-through head-mounted display (HMD). By using this system, the user can perform the exactitude of arm movement simply by moving his arms to follow and match the virtual arms, rendered from coach\'s movement of database, in the first-person view. To ensure the rendered virtual arms correctly aligned with the user\'s real shoulders, a calibration method is proposed to estimate the length of the user\'s arms and the positions of his head and shoulders in advance. In addition, we apply the system to Tai-Chi-Chuan practicing, our preliminary study has shown that the proposed egocentric hints can provide intuitive guidance for users to follow the arm movement of the coach with exactitude.
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.
Driver Assistance System Providing an Intuitive Perspective View of Vehicle Surrounding
(2015-01-01)
Yeh, Yen-Ting
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Peng, Chun-Kang
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Chen, Kuan-Wen
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Chen, Yong-Sheng
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Hung, Yi-Ping
Driver assistance systems can help drivers to avoid car accidents by providing warning signals or visual cues of surrounding situations. Instead of the fixed bird\'s-eye view monitoring proposed in many previous works, we developed a real-time vehicle surrounding monitoring system that can assist drivers to perceive the vehicle surrounding situations in third-person viewpoints. Four fisheye cameras were mounted around the vehicle in our system. We developed a simple and accurate fisheye camera calibration method to dewarp the captured images into perspective projection ones. Next, we estimated the intrinsic parameters of each undistorted virtual camera by using planar calibration patterns and then obtain the extrinsic camera parameters by using the global patterns on a ground plane. A new method was proposed to tackle the brightness uniformity problem caused by the various lighting conditions of cameras. Finally, we projected the undistorted images onto a 3D hybrid projection model, stitched these images together, and then rendered the images from a third-person viewpoint selected by the driver. The proposed hybrid projection model is composed of a paraboloid model and a columnar model and can achieve rendering results with less distortion. Compared to conventional around-vehicle monitoring systems, our system can provide adaptive, integrated, and intuitive views of vehicle surroundings in a more realistic way.
Dunhuang Mural Restoration using Deep Learning
(2018-01-01)
Wang, Han-Lei
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Han, Ping-Hsuan
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Chen, Yu-Mu
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Chen, Kuan-Wen
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Lin, XinYi
As time goes by, the art pieces inside Dunhuang Grottoes have suffered from tremendous damage such as mural deterioration, and they are usually difficult to be repaired. Although we can achieve digital preservation by modeling the caves and preserving mural as textures in virtual environment, we still cannot have a glimpse of how the grottoes look like without damage. In this work, we propose a systematic restoration framework, which is based on Generative Adversarial Network (GAN) technique, for these high-resolution but deteriorated mural textures. The main idea is to make the machine learn the transformation between deteriorated mural textures and restored mural textures. However, the resolution of training texture images (i.e. 8192x8192) is too high to be applied with GAN technology directly due to GPU RAM limitation. Instead, our method restores a set of high-resolution yet color-inconsistent textures patch-by-patch and a set of low-resolution but color-consistent full textures, and then combines them to get the final high-resolution and color-consistent result.
Estimating the Simulator Sickness in Immersive Virtual Reality with Optical Flow Analysis
(2017-01-01)
Lee, Jiun-Yu
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Han, Ping-Hsuan
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Tsai, Ling
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Peng, Rih-Ding
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Chen, Yang-Sheng
Fast and versatile algorithm for nearest neighbor search based on a lower bound tree
(2007-02-01)
Chen, Yong-Sheng
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Hung, Yi-Ping
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Yen, Ting-Fang
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Fuh, Chiou-Shann
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資訊工程學系
In this paper, we present a fast and versatile algorithm which can rapidly perform a variety of nearest neighbor searches. Efficiency improvement is achieved by utilizing the distance lower bound to avoid the calculation of the distance itself if the lower bound is already larger than the global minimum distance. At the preprocessing stage, the proposed algorithm constructs a lower bound tree (LB-tree) by agglorneratively clustering all the sample points to be searched. Given a query point, the lower bound of its distance to each sample point can be calculated by using the internal node of the LB-tree. To reduce the amount of lower bounds actually calculated, the winner-update search strategy is used for traversing the tree. For further efficiency improvement, data transformation can be applied to the sample and the query points. In addition to finding the nearest neighbor, the proposed algorithm can also (i) provide the k-nearest neighbors progressively; (ii) find the nearest neighbors within a specified distance threshold; and (iii) identify neighbors whose distances to the query are sufficiently close to the minimum distance of the nearest neighbor. Our experiments have shown that the proposed algorithm can save substantial computation, particularly when the distance of the query point to its nearest neighbor is relatively small compared with its distance to most other samples (which is the case for many object recognition problems). (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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.
Image Processing System For Integrating Multi-Resolution Images
(2008-06-19)
Hung, Yi-Ping
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Yeh, Wei-Shian
The image processing system for integrating multi-resolution images mainly applies several different multi-resolution image capture devices to extract the images from the observed scene and using the multi-resolution imaging devices to present the scene images relative to the observed scenes, respectively, by means of integration. In order to present a seamless image according to two different-resolution image sources, the coordinate conversions among the image capture devices, and among the imaging devices are mainly applied to extract and present the entire image to be able to resemble of having a single image capturing source and a single imaging source.
Lotus: Enhancing the Immersive Experience in Virtual Environment with Mist-based Olfactory Display
(2018-01-01)
Chen, Yang-Sheng
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Han, Ping-Hsuan
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Lee, Kong-Chang
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Hsieh, Chiao-En
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Hsiao, Jui-Chun
With the advance of virtual reality (VR) headset and haptic technologies, users can have a great experience when they are immersed in the virtual environment (VE). A fewer of research allow users to perceive the odor from the VE simultaneously. Based on the five senses, olfaction is one of the human sense that can perceive chemical information from the environment, which is also important for recreating the VE. In the past, some research groups have shown the techniques of olfactory display. However, to create the olfactory feedback for immersive VR when the user moving around in the tracking area, where a moveable display or a lightweight portable device is required, due to the user's nose is the only human receptor for perceiving the scent. We present Lotus, a steerable mist-based olfactory display with an airflow guiding module for simulating environments with olfaction. It can provide two kinds of VEs simultaneously for enhancing the immersive experience without carrying the weighty liquid.
One-Handed Input Through Rotational Motion for Smartwatches
(2018-01-01)
Tsai, Hsin-Ruey
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Chen, Po-Chang
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Chan, Liwei
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Hung, Yi-Ping
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資訊工程學系
One-handed input for smartwatches is crucial when users' hands are occupied. A rotational motion is leveraged, which can be detected by built-in motion sensors in most smartwatches, as input to provide item selection. Users control a cursor by rotating the smartwatch into different orientations using the proposed item selection gestures. To understand human wrist dexterity and the ability to perform rotational motion input along each degree of freedom on smartwatches, a human-factor study was performed. Except dexterity, users' consensus and agreement of user-defined rotational motion input gestures for selection and commitment on smartwatches in an exploratory user study were also observed. Based on both the studies, gestures roll and tilt are proposed as selection gestures, and shake and nod are used as commitment gestures. The item selection performance using the proposed gestures in 2D layouts in a user study was further evaluated. The study results showed that tilt-nod and tilt-shake are suitable for item numbers (4x3) and (5x5), respectively. Furthermore, due to high error rate for tilt-shake in (2x2) caused by false positive in shake detection, roll-shake with better social acceptance can be used as an alternative for smartwatches without a built-in front camera in (2x2).
Vision-Based Positioning for Internet-of-Vehicles
(2017-02)
Chen, Kuan-Wen
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Wang, Chun-Hsin
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Wei, Xiao
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Liang, Qiao
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Chen, Chu-Song
This paper presents an algorithm for ego-positioning by using a low-cost monocular camera for systems based on the Internet-of-Vehicles. To reduce the computational and memory requirements, as well as the communication load, we tackle the model compression task as a weighted k-cover problem for better preserving the critical structures. For real-world vision-based positioning applications, we consider the issue of large scene changes and introduce a model update algorithm to address this problem. A large positioning data set containing data collected for more than a month, 106 sessions, and 14 275 images is constructed. Extensive experimental results show that submeter accuracy can be achieved by the proposed ego-positioning algorithm, which outperforms existing vision-based approaches.