Giseok Kim

Study on Effective Visual Surveillance System using Dual-mode(Fixed+Pan/Tilt/Zoom) Camera

An effective dual-mode camera system(a passive wide-angle camera and a pan-tilt-zoom camera) is proposed in order to improve the performance of visual surveillance. The fixed wide-angle camera is used to monitor large open areas, but the moving objects on the images are too small to view in detail. And, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a specific moving target. However, its FOV (Field of View) is limited when zooming in on a specific target. Therefore, the cooperation of wide-angle and PTZ cameras is complementary. In this paper, we propose an automatic initial set-up algorithm and coordinate transform method from the wide-angle camera coordinate to the PTZ one, which are necessary to achieve the cooperation. The automatic initial set-up algorithm is able to synchronize the views of two cameras. When a moving object appears on the image plane of a wide-angle camera after the initial set-up positioning, the obtained values of the wide-angle camera should be transformed to the PTZ values based on the coordinate transform method. We also develope the PTZ control method. Various in-door and out-door experiments show that the proposed dual-camera system is feasible for the effective visual surveillance.

A Learning-based Visual Inspection System for Part Verification in a Panorama Sunroof Assembly Line using the SVM Algorithm

Abstract: This paper presents a learning-based visual inspection met hod that addresses the need for an improved adaptability ofa visual inspection system for parts verification in panorama sunroof assembly lines. It is essential to ensure that the manyparts required (bolts and nuts, etc.) are properly installed in the PLC sunroof manufacturing process. Instead of humaninspectors, a visual inspection system can automatically perform parts verification tasks to assure that parts are properly installedwhile rejecting any that are improperly assembled. The proposed visual inspection method is able to adapt to changinginspection tasks and environmental conditions through an efficient learning process. The proposed system consists of two majormodules: learning mode and test mode. The SVM (Support Vector Machine) learning algorithm is employed to implement partlearning and verification. The proposed method is very robust for changing environmental conditions, and various experimentalresults show the effectiveness of the proposed method.Keywords: visual inspection, part verification, panorama sunroof, support vector machine

Camera Calibration Method for an Automotive Safety Driving System

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car`s hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car`s hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

Real-time Temporal Synchronization and Compensation in Stereoscopic Video

In this paper, we propose a real-time temporal synchronization and compensation algorithm in stereoscopic video. Many temporal asynchronies are caused in the video editing stage and due to different transmission delays. These temporal asynchronies can degrade the perceived 3D quality. The goal of temporal alignment is to detect and to measure the temporal asynchrony and recover synchronization of the two video streams. In order to recover synchronization of the two video streams, we developed a method to detect asynchronies between the left and the right video streams based on a novel spatiogram information, which is a richer representation, capturing not only the values of the pixels but their spatial relationships as well. The proposed novel spatiogram additionally includes the changes of the spatial color distribution. Furthermore, we propose a block-based method for detection of the pair frame instead of one frame-based method. Various 3D experiments demonstrate the effectiveness of the proposed method.

Study on Viewpoint Estimation for Moving Parallax Barrier 3D Display

In this paper, we present an effective viewpoint estimation algorithm for the Moving parallax barrier method of 3D display mobile device. Moving parallax barrier is designed to overcome the biggest problem, the limited view angle. To accomplish it, the position of the viewer`s eyes or face should be estimated with strong stability and no latency. We focus on these requirements in the poor performance of mobile processors. We used a pre-processing algorithm in order to overcome the various illumination changes. And, we combined the conventional Viola-Jones face detection method and Optical-flow algorithm for robust and stable viewpoint estimation. Various computer simulations prove the effectiveness of the proposed method.

Robust Viewpoint Estimation Algorithm for Moving Parallax Barrier Mobile 3D Display

This paper presents a robust viewpoint estimation algorithm for Moving Parallax Barrier mobile 3D display in sudden illumination changes. We analyze the previous viewpoint estimation algorithm that consists of the Viola-Jones face detector and the feature tracking by the Optical-Flow. The sudden changes in illumination decreases the performance of the Optical-flow feature tracker. In order to solve the problem, we define a novel performance measure for the Optical-Flow tracker. The overall performance can be increased by the selective adoption of the Viola-Jones detector and the Optical-flow tracker depending on the performance measure. Various experimental results show the effectiveness of the proposed method.

Auto Parts Visual Inspection in Severe Changes in the Lighting Environment

This paper presents an improved learning-based visual inspection method for auto parts inspection in severe lighting changes. Automobile sunroof frames are produced automatically by robots in most production lines. In the sunroof frame manufacturing process, there is a quality problem with some parts such as volts are missed. Instead of manual sampling inspection using some mechanical jig instruments, a learning-based machine vision system was proposed in the previous research[1]. But, in applying the actual sunroof frame production process, the inspection accuracy of the proposed vision system is much lowered because of severe illumination changes. In order to overcome this capricious environment, some selective feature vectors and cascade classifiers are used for each auto parts. And we are able to improve the inspection accuracy through the re-learning concept for the misclassified data. The effectiveness of the proposed visual inspection method is verified through sufficient experiments in a real sunroof production line.

A Real-time Dual-mode Temporal Synchronization and Compensation based on Reliability Measure in Stereoscopic Video

In this paper, a real-time dual-mode temporal synchronization and compensation method based on a new reliability measure in stereoscopic video is proposed. The goal of temporal alignment is to detect the temporal asynchrony and recover synchronization of the two video streams. The accuracy of the temporal synchronization algorithm depends on the 3DTV contents. In order to compensate the temporal synchronization error, it is necessary to judge whether the result of the temporal synchronization is reliable or not. Based on our recently developed temporal synchronization method(1), we define a new reliability measure for the result of the temporal synchronization method. Furthermore, we developed a dual-mode temporal synchronization method, which uses a usual texture matching method and the temporal spatiogram method(1). The new reliability measure is based on two distinctive features, a dynamic feature for scene change and a matching distinction feature. Various experimental results show the effectiveness of the proposed method. The proposed algorithms are evaluated and verified through an experimental system implemented for 3DTV.

Automatinc synchronization of stereoscopic video for 3DTV broadcasting system

This paper proposes an algorithm to automatically detect synchronization error that can be occurred in the stereoscopic video system. Specially, this paper is aiming toward 3DTV broadcasting system that requires a real-time operation with high accuracy. Accordingly, we propose new similarity calculation algorithm by applying the spatiogram concept, which is proper to the sync error detection at stereoscopic video with real-time operation. In this paper, the spatiogram includes temporal information to increase an accuracy of sync error detection. This paper also introduces an implementation of stereoscopic video synchronizer for the purpose of practical use, which performs the sync error correction function. Finally, the proposed algorithms are evaluated and verified through an implemented of 3DTV experimental system.