• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.298-305
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• 2012

In this paper, we propose an integrated algorithm for scene recognition, which has been a challenging computer vision problem, with application to mobile robot localization. The proposed scene recognition method utilizes SIFT and visual words as local-level features and GIST as a global-level feature. As local-level and global-level features complement each other, it results in improved performance for scene recognition. This improved algorithm is of low computational complexity and robust to image distortions.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.482-487
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• 2007

실내의 완벽 주행이 주요 목적인 청소로봇은 자기 위치를 인식 할 수 있어야한다. 자기 위치를 제대로 인식하지 못하게 된다면 청소할 방을 모두 돌지 못하고 방 청소를 마치게 된다. 청소로봇이 상용화 되기 위해서는 저렴한 가격의 보드를 선호한다. 이것은 현재 나온 복잡한 계산을 요구하는 알고리즘을 사용하지 못하거나 사용하여도 속도가 느린 문제를 가진다. 영상 프레임 처리 속도가 느릴 경우 처리되는 동안 로봇이 움직이지 못하여 부드러운 움직임을 불가능하게 한다. 본 논문은 저사양의 하드웨어에서 자기 인식을 할 수 있는 시스템을 제안한다. 자기 인식을 하기 위해 처리 되어야 하는 전처리 과정과 전처리를 거친 데이터를 이용하여 자기 위치를 인식하도록 이동거리와 회전각을 계산하는 방법을 제안한다. 마지막으로 제안된 방법들을 이용하여 실제 이동 값과 비교, 분석한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.188-191
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• 2010

스테레오 매칭은 Robot Vision 분야에서 가장 활발하게 연구가 진행되어온 주제이다. 과거 많은 연구들은 스테레오 매칭 알고리즘의 정확도를 높이거나 처리속도를 개선하는 것 중 어느 한 쪽에만 집중하고 있었으며, 두 가지를 동시에 고려한 연구는 상대적으로 연구가 미흡한 실정이다. 본 논문에서는 영상의 공간적 중복 성질을 이용하여 스테레오 매칭 알고리즘의 처리속도를 획기적으로 개선하는 방법을 제안하고, 처리 속도 감소에 따라 증가되는 disparity map 추정 오차를 보상하는 기술을 제안한다. 구체적으로 Dynamic Programming (DP) 기반 스테레오 매칭 알고리즘에 제안한 속도 개선 방법을 적용하고, 개선된 Adaptive Support Weight Filter를 사용하여 보다 효과적인 오차 보상을 실현 하였다. 체계적인 실험을 통해, 본 논문에서 제안 하는 스테레오 매칭 알고리즘은 처리속도와 정확도를 동시에 개선할 수 있음을 검증하였다.

• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.339-348
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• 2010

One of the requirements for autonomous vehicles on off-road is to move stably in unstructured environments. Such capacity of autonomous vehicles is one of the most important abilities in consideration of mobility. So, many researchers use contact and/or non-contact methods to determine a terrain whether the vehicle can move on or not. In this paper we introduce an algorithm to classify terrains using visual information(one of the non-contacting methods). As a pre-processing, a contrast enhancement technique is introduced to improve classification of terrain. Also, for conducting classification algorithm, training images are grouped according to materials of the surface, and then Bayesian classification are applied to new images to determine membership to each group. In addition to the classification, we can build Traversability map specified by friction coefficients on which autonomous vehicles can decide to go or not. Experiments are made with Load-Cell to determine real friction coefficients of various terrains.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.414-427
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• 1990

This paper presents the development of the graphic simulator for an assembly workcell. The assembly workcell consists of two PUMA 560 manipulators, a conveyor belt system, a work table, and a vision sensor. In this study, the Petri Net theory is applied to model the assembly workcell and to construct the simulator. The event scheduling approach is used to simulate the cell. In order to show the graphic display of the simulation process, robot modelling, component modelling, and world modelling are included. The developed simulator is used to display the transition of the system state during the simulation. It is also used as a tool in selection the best resource states by studying the performance of the system as the resource states are changed.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2777-2779
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• 2005

최근 로봇 기술의 발전으로 인해 로봇에 관련된 제반 기술에 대한 연구가 활발히 진행되고 있다. 이러한 연구 중의 하나가 이동 로봇이 스스로 장애물을 감시하여 회피하도록 적절한 이동 경로를 생성해주는 연구이다. 따라서 본 논문에서는 이동 경로 상에 존재하는 장애물을 회피하기 위한 방법으로 비전 시스템에 기반하여 주행 거리 및 주행 시간을 최소화하여 목표점에 도달한 수 있도록 장애물을 회피하는 방법에 대하여 연구하였다. 시뮬레이션을 통해 제안한 방법의 성능을 검증하여보았다.

• ETRI Journal
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• v.35 no.6
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• pp.1021-1028
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• 2013

Automatic facial expression recognition is a widely studied problem in computer vision and human-robot interaction. There has been a range of studies for representing facial descriptors for facial expression recognition. Some prominent descriptors were presented in the first facial expression recognition and analysis challenge (FERA2011). In that competition, the Local Gabor Binary Pattern Histogram Sequence descriptor showed the most powerful description capability. In this paper, we introduce hybrid facial representations for facial expression recognition, which have more powerful description capability with lower dimensionality. Our descriptors consist of a block-based descriptor and a pixel-based descriptor. The block-based descriptor represents the micro-orientation and micro-geometric structure information. The pixel-based descriptor represents texture information. We validate our descriptors on two public databases, and the results show that our descriptors perform well with a relatively low dimensionality.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.299-301
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• 1996

Since a standard lens has small sight angle, a fish-eye lens can be used in order to obtain wide sight angle for the robot vision system. In spite of the advantage, the image through the lens has variable resolution; the central information of the lens is of high resolution, but the peripheral information is of low resolution. Owing to this difference of resolution, the variable resolution image should be transformed to a uniform resolution image in order to determine the positions of the objects in the image. In this work, the correction method for the distorted image is presented and the performance is analyzed. Furthermore, the camera with a fish eye lens can be used to determine the real world coordinates. The performance is shown through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1423-1426
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• 2005

Map building is the most important thing for the mobile robots navigation. It requires specific vision system such as CCD camera, range finding system, and many other things. Laser range finder has highly collimated beams can be obtained easily, thus achieving lateral resolution. Laser Diode is used for a continuous laser source. The Automatic Current Control Circuit and the Bias-T is used for mix AC signal with DC bias. This signal is used for driving Laser Diode. The main idea of the calculating distance is detecting phase shift between reference signal and detected signal by photo detector. For the signal processing, the Lock-in amplifier system is addressed in this paper. We used a diffused reflected beam to detect phase shift in this system. But this beam is minuteness signal so it can be easily buried in nose. Lock-in amplifier is used to measure the amplitude and phase of signals which are buried in noise.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1990-1993
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• 2005

Stereovision is known to be one of the most important tools for robot vision systems. Previously, 2D active contour model has been applied to stereovision by defining the contour on the 3D space instead of image plane. However, the proposed model is still that of curve so that some complex shapes such as surfaces with high curvature can not be properly estimated because of occlusion phenomena. In this paper, the authors extend the curve model to the surface model. The surface is approximated by polygons and new energy function and its optimization method for surface estimation is proposed. Its effectiveness is examined by experiments with real stereo images.