• 한국지능시스템학회논문지
• /
• 제12권2호
• /
• pp.97-102
• /
• 2002

본 논문에서는 CCD 칼라 영상을 이용하여 인간의 감성을 인식할 수 있는 방법을 제안한다. 먼저 CCD 카메라에 의해 획득한 칼라 영상으로부터 피부색 추출 방법을 이용하여 얼굴을 추출한다. 그 다음, 추출된 얼굴 영상으로부터 인간 얼굴의 특징점(눈썹, 눈, 코, 입) 들을 추출하는 방법과 각 특징점들 간의 구조적인 관계로부터 인간의 감성(놀람, 화남, 행복함, 슬픔)을 인식하는 방법을 제안한다. 본 논문에서 제안한 방법은 신경회로망을 이용하여 학습시킴으로써 인간의 감성을 인식한다. 마지막으로, 제안된 방법은 실험을 통해 그 응용 가능성을 확인한다.

• 제어로봇시스템학회논문지
• /
• 제20권11호
• /
• pp.1098-1102
• /
• 2014

Localization of aerial vehicles and map building of flight environments are key technologies for the autonomous flight of small UAVs. In outdoor environments, an unmanned aircraft can easily use a GPS (Global Positioning System) for its localization with acceptable accuracy. However, as the GPS is not available for use in indoor environments, the development of a SLAM (Simultaneous Localization and Mapping) system that is suitable for small UAVs is therefore needed. In this paper, we suggest a vision-based SLAM system that uses vision sensors and an AHRS (Attitude Heading Reference System) sensor. Feature points in images captured from the vision sensor are obtained by using GPU (Graphics Process Unit) based SIFT (Scale-invariant Feature Transform) algorithm. Those feature points are then combined with attitude information obtained from the AHRS to estimate the position of the small UAV. Based on the location information and color distribution, a Gaussian process model is generated, which could be a map. The experimental results show that the position of a small unmanned aircraft is estimated properly and the map of the environment is constructed by using the proposed method. Finally, the reliability of the proposed method is verified by comparing the difference between the estimated values and the actual values.

• 전기전자학회논문지
• /
• 제23권4호
• /
• pp.1166-1174
• /
• 2019

이 논문에서는 사람 재식별 모델인 PersonNet의 성능을 개선하는 방법을 제안하고 실험한다. 특징점 추출을 위해 인셉션 레이어를 접목하여, 기존 32개의 특징점을 154개로 증가시켜 강화하였다. 또한, PersonNet에서 사용하는 CND 방식을 수정하여 비대칭성을 완화하였고, 보행자 이미지의 특징점을 3부분으로 나누어 가중치를 적용한 방법을 적용하여 특징을 더 뚜렷하게 파악하도록 하였다. 성능 평가를 위해 CUHK01, CUHK03 그리고 Market-1501 3가지의 데이터베이스를 사용하였고 실험 결과 27~31% 성능이 개선되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권8호
• /
• pp.1843-1859
• /
• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• Journal of the Optical Society of Korea
• /
• 제15권1호
• /
• pp.30-37
• /
• 2011

Binocular-pair images obtained from two cameras can be used to calculate the three-dimensional (3D) world coordinate of a feature point. However, to apply this method, measurement accuracy of binocular vision depends on some structure factors. This paper presents an experimental study of measurement distance, baseline distance, and baseline direction. Their effects on camera reconstruction accuracy are investigated. The testing set for the binocular model consists of a series of feature points in stereo-pair images and corresponding 3D world coordinates. This paper discusses a method to increase the baseline distance of two cameras for enhancing the accuracy of a binocular vision system. Moreover, there is an inflexion point of the value and distribution of measurement errors when the baseline distance is increased. The accuracy benefit from increasing the baseline distance is not obvious, since the baseline distance exceeds 1000 mm in this experiment. Furthermore, it is observed that the direction errors deduced from the set-up are lower when the main measurement direction is similar to the baseline direction.

• 전자공학회논문지B
• /
• 제32B권10호
• /
• pp.1305-1313
• /
• 1995

In this paper, we propose a robust estimation of camera parameters from image sequence for high quality video composition. We first establish correspondence of feature points between consecutive image fields. After the establishment, we formulate a nonlinear least-square data fitting problem. When the image sequence contains moving objects, and/or when the correspondence establishment is not successful for some feature points, we get bad observations, outliers. They should be properly eliminated for a good estimation. Thus, we propose an iterative algorithm for rejecting the outliers and fitting the camera parameters alternatively. We show the validity of the proposed method using computer generated data sets and real image sequeces.

• Journal of Welding and Joining
• /
• 제21권1호
• /
• pp.60-65
• /
• 2003

At present. welding of most pipes with large diameter is carried out by the manual process. Automation of the welding process is necessary f3r the sake of consistent weld quality and improvement in productivity. In this study, two vision sensors, based on the optical triangulation, were used to obtain the information for seam tracking and detecting the weld defects. Through utilization of the vision sensors, noises were removed, images and 3D information obtained and positions of the feature points detected. The aforementioned process provided the seam and leg position data, calculated the magnitude of the gap, fillet area and leg length and judged the weld defects by ISO 5817. Noises in the images were removed by using the gradient values of the laser stripe's coordinates and various feature points were detected by using an algorithm based on the iterative polygon approximation method. Since the process time is very important, all the aforementioned processes should be conducted during welding.

• 전기학회논문지
• /
• 제59권12호
• /
• pp.2314-2318
• /
• 2010

For human-robot interaction, a robot should recognize the meaning of human behavior. In the case of static behavior such as face expression and sign language, the information contained in a single image is sufficient to deliver the meaning to the robot. In the case of dynamic behavior such as gestures, however, the information of sequential images is required. This paper proposes behavior classification by using fuzzy classifier to deliver the meaning of dynamic behavior to the robot. The proposed method extracts feature points from input images by a skeleton model, generates a vector space from a differential image of the extracted feature points, and uses this information as the learning data for fuzzy classifier. Finally, we show the effectiveness and the feasibility of the proposed method through experiments.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제49권6호
• /
• pp.307-315
• /
• 2000

For the autonomy of a mobile robot it is first needed to know its position and orientation. Various methods of estimating the position of a robot have been developed. However, it is still difficult to localize the robot without any initial position or orientation. In this paper we present the method how to make the colored map and how to calculate the position and direction of a robot using the angle data of an omnidirectional image. The wall of the map is rendered with the corresponding color images and the color histograms of images and the coordinates of feature points are stored in the map. Then a mobile robot gets the color omnidirectional image at arbitrary position and orientation, segments it and recognizes objects by multiple color indexing. Using the information of recognized objects robot can have enough feature points and localize itself.

• 한국정보처리학회논문지
• /
• 제6권4호
• /
• pp.1120-1128
• /
• 1999

모델을 이용한 물체인식을 모델영상들과 입력영상 간의 그래프 매칭과정으로 정의하였다. 본 논문에서는 그래프 매칭 문제를 최적화문제로 모델링하였고 최적화 문제해결을 위하여 유전자 알고리즘을 제안하였다. 이를 위하여 적합성함수, 자료구조, 유전연산자들이 개발되었다. 제안된 유전자 알고리즘이 이차원 영상에서 부분적으로 겹쳐진 물제들을 인식하기 위한 모델영상과 입력영상 간의 특징 점들을 일치시킴을 시뮬레이션을 통하여 보였다. 제안된 방법의 성능을 신경회로망을 이용한 방법과 비교하였다.