• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.1052-1055
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• 2002

동영상 정보는 영상정보뿐만이 아니라 음성정보, 문자정보 및 각종 의미있는 정보들을 포함하고 있어서 기존의 검색 방법으로는 사용자가 원하는 이미지를 찾는데 어려움이 따른다. 따라서, 본 연구에서는 동영상 정보의 효율적인 활용을 위한 색인 방법으로 MSE(Mean Square Error) 도입하여 동영상의 장면전환 검색하는 방법을 제안한다. 이것은 영상 데이터를 대각선 방향으로 일정픽셀의 칼라 값을 추출하여 행렬A에 i×j행렬로 i는 프레임 수, j는 프레임의 영상 높이로 저장하고 동영상의 전체 구조를 파악할 수 있도록 정지영상으로 샘플링 하였다. 샘플링 된 데이터는 대용량 동영상 데이터 이용에 있어서 사용자가 전체 동영상의 장면전환점을 한눈으로 파악할 수 있고, 각 프레임의 MSE와 임계값을 초과하면 그 프레임이 장면전환점으로 검색한다.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.202-204
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• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a Transformation algorithm of an Leg-wheel Hexapod Robot is proposed. Robot designed as can have advantages that do transfer possibility fast mobility in flat topography and uneven topography through walk that use wheel drive. In the proposed system, using the disparity data obtained from the left and right images captured by the stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Robot uses construed environmental data and transformation algorithm, decide wheel drive and leg waik, and can calculate width of street and regulate width of robot.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.381-382
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• 2007

대분분의 장면전환 검출방법은 복호화에 의한 연산량이 많고, 동영상의 매 프레임을 비교함으로 시간이 많이 소요되는 순차검색 방법이다. 이러한 문제를 해결하기 위해 압축 영역에서 시간적으로 표본화 하는 비 순차검색 방법들을 제안하였다. 비 순차검색방법은 동영상을 표본화 하는 검객간격이 중요한데 본 논문에서는 전체 동영상의 비교회수를 최소화하는 최적화된 검색간격을 구하고, 구한 검색간격을 사용하여 비 순차검색알고리즘을 제안한다. 제안한 알고리즘의 성능을 분석하기 위해 기존의 방법과 비교하여 성능의 우수성을 실험을 통해 분석하였다.

• Proceedings of the KSRS Conference
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• v.2
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• pp.594-597
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• 2006

Image co-registration is the process of overlaying two images of the same scene. One of which is a reference image, while the other (sensed image) is geometrically transformed to the one. Numerous methods were developed for the automated image co-registration and it is known as a time-consuming and/or computation-intensive procedure. In order to improve efficiency and effectiveness of the co-registration of satellite imagery, this paper proposes a pre-qualified area matching, which is composed of feature extraction with Laplacian filter and area matching algorithm using correlation coefficient. Moreover, to improve the accuracy of co-registration, the outliers in the initial matching point should be removed. For this, two outlier detection techniques of studentized residual and modified RANSAC algorithm are used in this study. Three pairs of Landsat images were used for performance test, and the results were compared and evaluated in terms of robustness and efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1055-1058
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is the use of different model (CAD model etc.) known a priori. Also fusion or multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Voting-based fusion of cues is adapted. In voting. a very simple or no model is used for fusion. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters. namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.360-362
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• 2009

In this paper, we studied for the real-time azimuthal measurement of HMD(Head Mounted Display) using the feature points detection to control the tele-operated vision system on the mobile robot. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.867-868
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• 2008

In this paper, we discuss face verification using the optimum nonlinear composite filter. The optimum nonlinear composite filter is derived by minimizing the output energy due to the additive noise and the input scene. We construct the nonlinear composite filter with 3 training images. The performance is analyzed in terms of the detection probability and the false alarm probability showing the robustness to distortion and noise.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.10
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• pp.67-75
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• 1997

A design for a system to perform rapid recognition of three dimensional objects is presented, focusing on efficient indexing. In order to retrieve the best matched models without exploring all possible object matches, we have employed a bayesian framework. A decision-theoretic measure of the discriminatory power of a feature for a model object is defined in terms of posterior probability. Detectability of a featrue defined as a function of the feature itselt, viewpoint, sensor charcteristics, nd the feature detection algorithm(s) is also considered in the computation of discribminatory power. In order to speed up the indexing or selection of correct objects, we generate and verify the object hypotheses for rfeatures detected in a scene in the order of the discriminatory power of these features for model objects.

• ETRI Journal
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• v.38 no.3
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• pp.502-509
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• 2016

Feature detection and description are key ingredients of common image processing and computer vision applications. Most existing algorithms focus on robust feature matching under challenging conditions, such as inplane rotations and scale changes. Consequently, they usually fail when the scene is blurred by camera shake or an object's motion. To solve this problem, we propose a new feature description algorithm that is robust to image blur and significantly improves the feature matching performance. The proposed algorithm builds a feature descriptor by considering the integral projection along four angular directions ($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, and $135^{\circ}$) and by combining four projection vectors into a single highdimensional vector. Intensive experiment shows that the proposed descriptor outperforms existing descriptors for different types of blur caused by linear motion, nonlinear motion, and defocus. Furthermore, the proposed descriptor is robust to intensity changes and image rotation.

• ETRI Journal
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• v.42 no.3
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• pp.399-410
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• 2020

Detecting visual relationships in an image is important in an image understanding task. It enables higher image understanding tasks, that is, predicting the next scene and understanding what occurs in an image. A visual relationship comprises of a subject, a predicate, and an object, and is related to visual, language, and spatial cues. The predicate explains the relationship between the subject and object and can be categorized into different categories such as prepositions and verbs. A large visual gap exists although the visual relationship is included in the same predicate. This study improves upon a previous study (that uses language cues using two losses) and a spatial cue (that only includes individual information) by adding relative information on the subject and object of the extant study. The architectural limitation is demonstrated and is overcome to detect all zero-shot visual relationships. A new problem is discovered, and an explanation of how it decreases performance is provided. The experiment is conducted on the VRD and VG datasets and a significant improvement over previous results is obtained.