Browsing by Author "Shih, Shen-En"

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A Convenient Vision-Based System for Automatic Detection of Parking Spaces in Indoor Parking Lots Using Wide-Angle Cameras
(2014-07-01)
Shih, Shen-En
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Tsai, Wen-Hsiang
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交大名義發表
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資訊工程學系
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National Chiao Tung University
A convenient indoor vision-based parking lot system using wide-angle fisheye-lens or catadioptric cameras is proposed, which is easy to set up by a user with no technical background. Easiness in the system setup mainly comes from the use of a new camera model that can be calibrated using only one space line without knowing its position and direction, as well as from the allowance of convenient changes in detected parking space boundaries. After camera calibration based on the new camera model is completed, parking space boundary lines are automatically extracted from input wide-angle images by a modified Hough transform with a new cell accumulation scheme, which can generate more accurate equal-width curves using the geometric relations of line positions and directions. In addition, the user may easily add or remove the boundary lines by single clicks on images, and parking spaces can be segmented out by region growing with the use of the boundary lines. Finally, vacant parking spaces can be detected by a background subtraction scheme. A real vision-based parking lot has been established and relevant experiments conducted. Good experimental results show the correctness, feasibility, and robustness of the proposed methods.
A New Two-Omni-Camera System with a Console Table for Versatile 3D Vision Applications and Its Automatic Adaptation to Imprecise Camera Setups
(2011)
Shih, Shen-En
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Tsai, Wen-Hsiang
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資訊工程學系
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Department of Computer Science
A new two-omni-camera system for 3D vision applications and a method for adaptation of the system to imprecise camera setups are proposed in this study. First, an efficient scheme for calibration of several omni-camera parameters using a set of analytic formulas is proposed. Also proposed is a technique to adapt the system to imprecise camera configuration setups for in-field 3D feature point data computation. The adaptation is accomplished by the use of a line feature of the console table boundary. Finally, analytic formulas for computing 3D feature point data after adaptation are derived. Good experimental results are shown to prove the feasibility and correctness of the proposed method.
A Two-Omni-Camera Stereo Vision System With an Automatic Adaptation Capability to Any System Setup for 3-D Vision Applications
(2013-07-01)
Shih, Shen-En
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Tsai, Wen-Hsiang
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資訊工程學系
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Department of Computer Science
A stereo vision system using two omni-cameras for 3-D vision applications is proposed, which has an automatic adaptation capability to any system setup before 3-D data computation is conducted. The adaptation, which yields the orientations and distance of the two omni-cameras, is accomplished by detecting and analyzing the horizontal lines appearing in the omni-images acquired with the cameras and a person standing in front of the cameras. Properties of line features in environments are utilized for detecting more precisely the horizontal lines that appear as conic sections in omni-images. The detection work is accomplished through the use of carefully chosen parameters and a refined Hough transform technique. The detected horizontal lines are utilized to compute the cameras' orientations and distance from which the 3-D data of space points are derived analytically. Compared with a traditional system using a pair of projective cameras with nonadjustable camera orientations and distance, the proposed system has the advantages of offering more flexibility in camera setups, better usability in wide areas, higher precision in computed 3-D data, and more convenience for nontechnical users. Good experimental results show the feasibility of the proposed system.
HOUGH TRANSFORM WITH DYNAMIC THRESHOLDING FOR ROBUST AND REAL-TIME DETECTION OF COMPLEX CURVES IN IMAGES
(2013)
Shih, Shen-En
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Tsai, Wen-Hsiang
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資訊工程學系
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Department of Computer Science
A dynamic thresholding method is proposed for use in the Hough transform to detect complex curves in images robustly. While determining edge pixels contributing to the peak in the Hough space for detecting a curve with noise and other errors, the proposed method can endure the errors by detecting pixels coming from an equal-width shape which is centered at the curve with a small width everywhere along the curve. This equal-width shape detection capability is accomplished by the use of a dynamic threshold for pixel selection, which is derived from the use of the first-order directional derivative of the function describing the curve. Three conventional methods are compared to show the superiority in robustness of the proposed method via experimental results, and a real-time application of the method for quick detection of lines in omni-images is also demonstrated.
Optimal Design and Placement of Omni-Cameras in Binocular Vision Systems for Accurate 3-D Data Measurement
(2013-11-01)
Shih, Shen-En
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Tsai, Wen-Hsiang
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資訊工程學系
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Department of Computer Science
A new problem of automatically designing an optimal stereo vision system using two omni-directional catadioptric cameras to yield the highest 3-D data accuracy is studied. Factors of the system configuration considered in the design include camera pose, field of vision, and mirror shape. To find the optimal vision system configuration, an analytic formula is derived to model the 3-D measurement error, which takes into consideration the variations of pixel-quantization precisions and angular resolutions in images by conducting error propagation analysis in the data computation process. The formula is then used in an optimization framework to find the optimal system configurations for different shapes of system setup environments. For regular cases with rectangular cuboid-shaped 3-D measurement and camera placement areas, two fast algorithms are proposed to solve the problem, one being bisection-based and relatively slower for deriving the optimal solution, and the other faster using analytic formulas for deriving a suboptimal solution that is proved to be close to the optimal one in precision. Experimental results of simulations and real application cases show the feasibility of the proposed method.