Browsing by Author "Tsai, Chi-Yi"

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A new edge-adaptive demosaicing algorithm for color filter arrays
(2007-09-01)
Tsai, Chi-Yi
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Song, Kai-Tai
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電控工程研究所
;
Institute of Electrical and Control Engineering
A novel edge-adaptive demosaicing algorithm (EADA) is proposed in this paper to effectively reduce color artifacts in demosaiced images from a color filter array (CFA). The proposed algorithm aims to reduce the aliasing error in red and blue channels by exploiting high-frequency information of the green channel. To achieve this, color-difference based edge-adaptive filtering and post-processing schemes are designed to reproduce the color values by exploiting the green channel information. For green channel interpolation, any of the existing image interpolation methods can be used and combined with the proposed algorithm. Moreover, a new adaptive interpolation method is presented for reconstructing the green channel from CFA samples. We have compared this technique with two recently proposed demosaicing techniques: Gunturk's and Lu's methods. The experimental results show that EADA outperforms both of them in both PSNR values and CIELAB Delta E*(ab) measures. (C) 2007 Elsevier B.V. All rights reserved.
Development of the Robot of Living Aid: RoLA
(2008)
Song, Kai-Tai
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Tsai, Chi-Yi
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Huang, Fu-Sheng
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Hong, Jung-Wei
;
Lin, Chen-Yang
With increasing number of aging people, taking care of the elderly will become more and more important for future society, especially for those elderly living alone. This paper presents an autonomous mobile robot Rola (Robot of LivingAid), which can handle certain emergency conditions in a home setting to help the elderly through multi-modal sensing and control functions. The implemented functions include visual tracking, video transmission, location aware, navigation, body pose recognition and emergency call out. Rola can accommodate smoothly to the movement of a user through face tracking and performs robot-assisted video conferencing. Rola follows the elderly in the living room using the developed RF-based location aware system. It avoids obstacles in a narrow space employing a laser scanner. Further, Rola can help the elderly as he/she falls down at home. This accidental situation can be detected with a tri-axial accelerometer mounted on the waist of the elderly. It approaches to the elderly by the help of location-aware system and provides timely help through automatic call out and wireless video transmission.
Dynamic visual tracking control of a mobile robot with image noise and occlusion robustness
(2009-07-02)
Tsai, Chi-Yi
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Song, Kai-Tai
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電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a robust visual tracking control design for a nonholonomic mobile robot equipped with a tilt camera. This design aims to allow the mobile robot to keep track of a dynamic moving target in the camera's field-of-view; even though the target is temporarily fully occluded. To achieve this, a control system consisting of a visual tracking controller (VTC) and a visual state estimator (VSE) is proposed. A novel visual interaction model is derived to facilitate the design of VTC and VSE. The VSE is responsible for estimating the optimal target state and target image velocity in the image space. The VTC then calculates the corresponding command velocities for the mobile robot to work in the world coordinates. The proposed VSE not only possesses robustness against the image noise, but also overcomes the temporary occlusion problem. Computer simulations and practical experiments of a mobile robot to track a moving target have been carried out to validate the performance and robustness of the proposed system. (C) 2008 Elsevier B.V. All rights reserved.
Face tracking interaction control of a nonholonomic mobile robot
(2006)
Tsai, Chi-Yi
;
Song, Kai-Tai
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a novel face tracking control scheme for human-robot interaction control in image plane. This control scheme is robust to the velocity quantization error in practical implementation. A visual tracking controller is designed for ensuring global asymptotic stability of the closed-loop visual tracking system based on an error-state control model in image plane. In order to overcome the quantization uncertainty encountered in practical systems, an image-based robust control law is proposed to guarantee the stability of the robotic control system based on Lyapunov theory. This design provides a useful solution for smooth visual tracking control of slow-motion robots in a home setting. Simulation and Experimental results verify the effectiveness of the proposed visual tracking control scheme, both in terms of tracking performance and system convergence.
Heterogeneity-projection hard-decision color interpolation using spectral-spatial correlation
(2007-01-01)
Tsai, Chi-Yi
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Song, Kai-Tai
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電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a novel heterogeneity-projection hard-decision (HPHD) color interpolation procedure for reproduction of Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which each pixel only needs to be interpolated once. A new heterogeneity-projection scheme based on a novel spectral-spatial correlation concept is proposed to estimate the best interpolation direction directly from the original mosaic image. Using the proposed heterogeneity-projection scheme, a hard-decision rule can be decided before performing the interpolation. The advantage of this scheme is that it provides an efficient way for decision-based algorithms to generate improved results using fewer computations. Compared with three recently reported demosaicing techniques, Gunturk's, Lu's, and Li's methods, the proposed HPHD outperforms all of them in both PSNR values and S-CIELAB Delta E-ab* measures by utilizing 25 natural images from Kodak PhotoCD.
Heterogeneity-projection hard-decision interpolation method for color reproduction
(2008-03-13)
Tsai, Chi-Yi
;
Song, Kai-Tai
The present invention discloses a heterogeneity-projection hard-decision interpolation method for color reproduction, which utilizes a heterogeneity-projection method to determine the optimal edge direction and then utilizes a hard-decision rule to determine the optimal interpolation direction and obtain the information of the green color elements. The high-frequency information of the plane of the green color elements is incorporated into the processing of the planes of the red color elements and the blue color elements to reduce the restoration errors of the red and blue color elements. Therefore, the present invention can decrease the interpolation-direction errors and achieve a higher PSNR and a better visual effect.
Multi-Robot Cooperative Sensing and Localization
(2008)
Song, Kai-Tai
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Tsai, Chi-Yi
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Huang, Cheng-Hsien Chiu
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電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a novel method for mobile robot localization based on multi-robot cooperative sensing. A multi-robot cooperative localization scheme is proposed using visual detection and sensor data fusion. The visual detection system employs a stereo vision module for both observing other robots and obtaining environmental information. Each mobile robot is able to recognize its teammates by using the vision system. The localization error is reduced through the proposed sensor fusion algorithm. The cooperative localization algorithm consists of two stages: serial fusion and parallel fusion. Serial fusion aims to identify the positional uncertainty of an observed robot while parallel fusion reduces its positional error based on Kalman filtering. The multi-robot cooperative localization system has been realized through the server-client architecture. Experimental results are presented to validate the effectiveness of the proposed algorithms.
NURSING SYSTEM
(2009-08-06)
Tsai, Chi-Yi
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Huang, Fu-Sheng
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Lin, Chen-Yang
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Lin, Zhi-Sheng
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Chen, Chun-Wei
A nursing system of the present invention can position where a person to be nursed through a sensor network widely deployed in an environment, instantaneously detect if the person to be nursed has an accident, and forward a message to inform a relative or medical staff. An autonomous robot will actively move beside the person to be nursed and transmit real-time images to a remote computer or PDA so that the relative or medical staff can swiftly ascertain the situation of the person to be nursed and the person to be nursed in case of emergency can be rescued as soon as possible.
ROBUST FACE TRACKING CONTROL OF A MOBILE ROBOT USING SELF-TUNING KALMAN FILTER AND ECHO STATE NETWORK
(2010-07-01)
Tsai, Chi-Yi
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Dutoit, Xavier
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Song, Kai-Tai
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Van Brussel, Hendrik
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Nuttin, Marnix
This paper presents a novel design of face tracking algorithm and visual state estimation for a mobile robot face tracking interaction control system. The advantage of this design is that it can track a user's face under several external uncertainties and estimate the system state without the knowledge about target's 3D motion-model information. This feature is helpful for the development of a real-time visual tracking control system. In order to overcome the change in skin color due to light variation, a real-time face tracking algorithm is proposed based on an adaptive skin color search method. Moreover, in order to increase the robustness against colored observation noise, a new visual state estimator is designed by combining a Kalman filter with an echo state network-based self-tuning algorithm. The performance of this estimator design has been evaluated using computer simulation. Several experiments on a mobile robot validate the proposed control system.
Robust mobile robot visual tracking control system using self-tuning Kalman filter
(2007)
Tsai, Chi-Yi
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Song, Kai-Tai
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Dutoit, Xavier
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Van Brussel, Hendrik
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Nuttin, Marnix
This paper presents a novel design of a robust visual tracking control system, which consists of a visual tracking controller and a visual state estimator. This system facilitates human-robot interaction of a unicycle-modeled mobile robot equipped with a tilt camera. Based on a novel dual-Jacobian visual interaction model, a dynamic motion target can be tracked using a single visual tracking controller without target's 3D velocity information. The visual state estimator aims to estimate the optimal system state and target image velocity, which is used later by the visual tracking controller. To achieve this, a self-tuning Kalman filter is proposed to estimate interesting parameters online in real-time. Further, because the proposed method is fully working in image space, the computational complexity and the sensor/camera modeling errors can be reduced. Experimental results validate the effectiveness of the proposed method, in terms of tracking performance, system convergence, and robustness.
Robust visual tracking control of mobile robots based on an error model in image plane
(2005)
Tsai, Chi-Yi
;
Song, Kai-Tai
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a novel visual tracking control scheme, which is robust to the quantization error in practical implementation. The proposed control scheme is based on an error model of camera-object visual interaction in image plane for unicycle mobile robots. In order to overcome the quantization error encountered in practical system, a stability necessary condition for ensuring global asymptotic stability of the closed-loop visual tracking system is derived through Lyapunov's direct method. The robust control law is then proposed to guarantee that the visual tracking system satisfies the stability necessary condition based on Lyapunov theory. Experimental results verify the effectiveness of the proposed control scheme, both in terms of tracking performance and system convergence.
Robust visual tracking control system of a mobile robot based on a dual-Jacobian visual interaction model
(2009-06-30)
Tsai, Chi-Yi
;
Song, Kai-Tai
;
Dutoit, Xavier
;
Van Brussel, Hendrik
;
Nuttin, Marnix
This paper presents a novel design of a robust visual tracking control system, which consists of a visual tracking controller and a visual state estimator. This system facilitates human-robot interaction of a unicycle-modeled mobile robot equipped with a tilt camera. Based on a novel dual-Jacobian visual interaction model, a robust visual tracking controller is proposed to track a dynamic moving target. The proposed controller not only possesses some degree of robustness against the system model uncertainties, but also tracks the target without its 3D velocity information. The visual state estimator aims to estimate the optimal system state and target image velocity, which is used by the visual tracking controller. To achieve this, a self-tuning Kalman filter is proposed to estimate interesting parameters and to overcome the temporary occlusion problem. Furthermore, because the proposed method is fully working in the image space, the computational complexity and the sensor/camera modeling errors can be reduced. Experimental results validate the effectiveness of the proposed method, in terms of tracking performance, system convergence, and robustness. (C) 2009 Elsevier B.V. All rights reserved.
Speaker attention system for mobile robots using microphone array and face tracking
(2006)
Song, Kai-Tai
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Hu, Jwu-Sheng
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Tsai, Chi-Yi
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Chou, Chung-Min
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Cheng, Chieh- Cheng
This paper presents a real-time human-robot interface system (HRIS), which processes both speech and vision information to improve the quality of communication between human and an autonomous mobile robot. The HRIS contains a real-time speech attention system and a real-time face tracking system. In the speech attention system, a microphone-array voice acquisition system has been developed to estimate the direction of speaker and purify the speaker's speech signal in a noisy environment. The developed face tracking system aims to track the speaker's face under illumination variation and react to the face motion. The proposed HRIS can provide a robot with the abilities of finding a speaker's direction, tracking the speaker's face, moving its body to the speaker, focusing its attention to the speaker who is talking to it, and purifying the speaker's speech. The experimental results show that the HRIS not only purifies speech signal with a significant performance, but also tracks a face under illumination variation in real-time.
Visual state estimation using self-tuning Kalman filter and echo state network
(2008)
Tsai, Chi-Yi
;
Dutoit, Xavier
;
Song, Kai-Tai
;
Van Brussel, Hendrik
;
Nuttin, Marnix
This paper presents a novel design of visual state estimation for an image-based tracking control system to estimate system state during visual tracking control process. The advantage of this design is that it can estimate the target status and target image velocity without using the knowledge of target's 3D motion-model information. This advantage is helpful for real-time visual tracking controller design. In order to increase the robustness against random observation noise, a neural network based self-tuning algorithm is proposed using echo state network (ESN) technique. The visual state estimator is designed by combining a Kalman filter with the ESN-based self-tuning algorithm. The performance of this estimator design has been evaluated using computer simulation. Several interesting experiments on a mobile robot validate the proposed algorithms.
Visual Tracking Control of a Wheeled Mobile Robot With System Model and Velocity Quantization Robustness
(2009-05-01)
Tsai, Chi-Yi
;
Song, Kai-Tai
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a visual tracking control design of a nonholonomic mobile robot equipped with a tilt camera. The proposed design enhances various image-tracking applications using an on-board monocular camera, such as human-robot interaction and surveillance. Based on Lyapunov theory, the proposed control scheme not only possesses some degree of robustness against parametric uncertainty, but also overcomes the external uncertainty caused by velocity quantization noise. Moreover, the proposed controller fully works in the image space; hence, the computational complexity and the effects of sensor/camera modeling errors can be greatly reduced. Experimental results validate the effectiveness of the proposed control scheme, in terms of tracking performance, system convergence, and robustness.