• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.436-442
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• 2016

There are a lot of sports when you left the victory and the defeat of the match the referee subjective judgment. In particular, TaeKwonDo pumse How accurate a given action? Is important. Objectively evaluate the subjective opinion of victory and defeat in a sporting event and the technology to keep as evidence is required. This study was implemented a system for recognizing Taekwondo executed through the number of motion recognition device. Step Sensor also used to detect a user's location. This study evaluated the rate matching the standard gesture data and the motion data. Through multiple gesture recognition equipment was more accurate assessment of the Taekwondo action.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.33-36
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• 2000

To create a more realistic soccer game derived from TV images, we are developing an image synthesis system that generates 3D image sequence from TV images. We propose the method for the team and the pose recognition of players in TV images. The representation includes camera calibration method, team recognition method and pose recognition method. To find the location of a player on the field, a field model is constructed and a player's field position is transformed by 4-feature points. To recognize the team information of players, we compute RGB mean values and standard deviations of a player in TV images. Finally, to recognize pose of a player, this system computes the velocity and the ratio of player(height/width). Experimental results are included to evaluate the performance of the team and the pose recognition.

• 반도체디스플레이기술학회지
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• 제12권1호
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• pp.1-7
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• 2013

Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.

• 한국산학기술학회논문지
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• 제14권4호
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• pp.1988-1992
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• 2013

본 논문에서는 일정 지역 내에 진입한 영상 객체에 대한 객체인지 방안을 제안한다. 이 방안은 특정 지역내에 진입한 객체의 행동 패턴을 검출하고 추적하는 응용 모듈에 필요하다. 객체인지에 대한 부분은 여러 응용 모듈에서 적용될 수 있는 방안으로 단순히 영상 정보의 인식 범위에서 실제 좌표에 대한 인식으로의 확대를 위한 것이다. GPS 좌표와 영상 정보의 정합을 통하여 개체의 위치 좌표를 추출함으로서 지정 영역에서 인지된 객체의 위치를 탐색한다.

• 로봇학회논문지
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• 제3권1호
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• 로봇학회논문지
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• 제6권3호
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• pp.247-254
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• 2011

This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment.

• 전자공학회논문지B
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• 제32B권9호
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• pp.1171-1180
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• 1995

In this paper, we present a 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In object modeling step, the features for recognition are extracted from the CAD models of objects to be recognized. Since the approach is based on the CAD models, the accuracy and flexibility are greatly improved. In matching stage, the sensed image is compared with the stored model, which is assumed to yield a distortion (location and orientation) in the 3-D Hough transform domain. The high dimensional (6-D) parameter space, which defines the distortion, is decomposed into the low dimensional space for an efficient recognition. At first we decompose the distortion parameter into the rotation parameter and the translation parameter, and the rotation parameter is further decomposed into the viewing direction and the rotational angle. Since we use the 3-D Hough transform domain of the input images directly, the sensitivity to the noise and the high computational complexity could be significantly alleviated. The results show that the proposed 3-D object recognition system provides a satisfactory performance on the real range images.

• 한국정보통신학회논문지
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• 제16권7호
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• pp.1549-1558
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• 2012

위치 인식 시스템은 물류, 의료, 홈 네트워크, 군사, 교통 시스템 등 다양한 분야에서 활용된다. 본 논문에서는 무선 RF만으로 정밀한 위치 인식이 가능한 IEEE802.15.4a의 CSS(Chirp Spread Spectrum)방식을 기반으로 다양한 환경에서 사용할 수 있는 위치인식 시스템을 설계하였다. 실험 결과 20m의 반경을 가지는 공간에서 0.5m 미만의 오차범위를 가지는 위치 인식 시스템을 구현하였다.

• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.344-351
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• 2016

Recently, mobile application for english vocabulary learning is being developed actively. However, most mobile English vocabulary learning applications did not effectively connected with the technical advantages of mobile learning. Also,the study of mobile english vocabulary learning app are still insufficient. Therefore, this paper development a english vocabulary context-learning Agent that can practice context learning more reasonably using a location-based service, a character recognition technology and augmented reality technology based on smart phones. In order to evaluate the performance of the proposed agent, we have measured the precision and usability. As results of experiments, the precision of learning vocabulary is 89% and 'Match between system and the real world', 'User control and freedom', 'Recognition rather than recall', 'Aesthetic and minimalist design' appeared to be respectively 3.91, 3.80, 3.85, 4.01 in evaluation of usability. It were obtained significant results.

• 한국소음진동공학회논문집
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• 제23권9호
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• pp.814-822
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• 2013

For the fault diagnosis of a mechanical system, pattern recognition methods have being used frequently in recent research. Hidden Markov model(HMM) and artificial neural network(ANN) are typical examples of pattern recognition methods employed for the fault diagnosis of a mechanical system. In this paper, a hybrid method that combines HMM and ANN for the fault diagnosis of a mechanical system is introduced. A rotating blade which is used for a wind turbine is employed for the fault diagnosis. Using the HMM/ANN hybrid model along with the numerical model of the rotating blade, the location and depth of a crack as well as its presence are identified. Also the effect of signal to noise ratio, crack location and crack size on the success rate of the identification is investigated.