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Contrast map과 Salient point를 이용한 중요객체 자동추출
곽수영(Sooyeong Kwak),고병철(Byoungchul Ko),변혜란(Hyeran Byun) 한국정보과학회 2004 한국정보과학회 학술발표논문집 Vol.31 No.1B
본 논문에서는 Contrast map과 Salient point를 이용하여 영상에서 중요한 객체를 자동으로 추출하는 방법을 제안한다. 우선 인간의 시각 체계와 유사한 밝기(luminance), 색상(color) 그리고 방향성 (orientation) 3가지의 특징정보를 이용하여 각각의 특징정보로부터 feature map을 생성하고, 이 3가지의 feature map을 선형 결합하여 contrast map을 생성한다. 이렇게 생성된 하나의 contrast map을 이용하여 대략적인 Attention Window (AW)의 위치를 결정 한다. 다음으로, 영상으로부터 웨이블릿 변환을 적용하여 salient point를 찾고, salient point의 분포와 contrast map의 중요도에 따라 AW의 크기를 실제 중요 객체의 크기와 가장 유사하도록 축소시킨다. 이렇게 선택되고 축소된 AW안에서 실제 중요 객체를 추출하기 위해 AW 내부에 존재하는 영상에 대해서만 영상 분할을 하고 불필요한 영역을 제거하여 자동으로 중요객체를 추출하도록 한다.
후미등 하단 학습기반의 차종에 무관한 전방 차량 검출 시스템
기민송(Minsong Ki),곽수영(Sooyeong Kwak),변혜란(Hyeran Byun) 한국방송·미디어공학회 2016 방송공학회논문지 Vol.21 No.4
Recently, there are active studies on a forward collision warning system to prevent the accidents and improve convenience of drivers. For collision evasion, the vehicle detection system is required. In general, existing learning-based vehicle detection methods use the entire appearance of the vehicles from rear-view images, so that each vehicle types should be learned separately since they have distinct rear-view appearance regarding the types. To overcome such shortcoming, we learn Haar-like features from the lower part of the vehicles which contain tail lights to detect vehicles leveraging the fact that the lower part is consistent regardless of vehicle types. As a verification procedure, we detect tail lights to distinguish actual vehicles and non-vehicles. If candidates are too small to detect the tail lights, we use HOG(Histogram Of Gradient) feature and SVM(Support Vector Machine) classifier to reduce false alarms. The proposed forward vehicle detection method shows accuracy of 95% even in the complicated images with many buildings by the road, regardless of vehicle types.
강주형(Joohyung Kang),곽수영(Sooyeong Kwak) 한국방송·미디어공학회 2015 방송공학회논문지 Vol.20 No.3
The demand of violence detection techniques using a video analysis to help prevent crimes is increasing recently. Many researchers have studied vision based behavior recognition but, violent behavior analysis techniques usually focus on violent scenes in television and movie content. Many methods previously published usually used both a color(e.g., skin and blood) and motion information for detecting violent scenes because violences usually involve blood scenes in movies. However, color information (e.g., blood scenes) may not be useful cues for violence detection in surveillance videos, because they are rarely taken in real world situations. In this paper, we propose a method of violent behavior detection in surveillance videos using motion vectors such as flow vector magnitudes and changes in direction except the color information. In order to evaluate the proposed algorithm, we test both USI dataset and various real world surveillance videos from YouTube.
박준욱(Junwook Park),곽수영(Sooyeong Kwak) 한국방송·미디어공학회 2013 방송공학회논문지 Vol.18 No.3
A method to classify a golf swing motion into 7 sections using a Kinect sensor and a fuzzy system is proposed. The inputs to the fuzzy logic are the positions of golf club and its head, which are extracted from the information of golfers joint position and color information obtained by a Kinect sensor. The proposed method consists of three modules: one for extracting the joints information, another for detecting and tracking of a golf club, and the other for classifying golf swing motions. The first module extracts the hands position among the joint information provided by a Kinect sensor. The second module detects the golf club as well as its head with the Hough line transform based on the hands coordinate. Using a fuzzy logic as a classification engine reduces recognition errors and, consequently, improves the performance of robust classification. From the experiments of real-time video clips, the proposed method shows the reliability of classification by 85.2%.
HOG-SP를 이용한 방향지시기호 인식 및 향상된 차선 검출
이명우(Myungwoo Lee),곽수영(Sooyeong Kwak),변혜란(Hyeran Byun) 한국방송·미디어공학회 2016 방송공학회논문지 Vol.21 No.1
Recently, there is a need for automatic recognition of a variety of symbols on roads because of activation of information services using digital maps on the Web or mobile devices. This paper proposes a method which automatically recognizes 11 kinds of symbolic road markings on the road surface with HOG-SP(Histogram of oriented Gradients-Split Projection) descriptor and shows improvement of lane position detection with recognized symbolic road markings. With the proposed method, recognition rate of 81.99% has been proven on NAVER road view images and the experiments proves the superiority of proposed method by comparisons with other existing methods. Moreover, this paper shows 7.64% higher lane position detection rate by recognizing road surface marking beforehand than only detecting lanes positions.
원주호(Joo Ho Won),곽수영(Sooyeong Kwak),고형호(Hyungho Ko) 대한전자공학회 2016 대한전자공학회 학술대회 Vol.2016 No.6
Electronics used for aerospace application have to be complied to stringent requirement for reliable operation in harsh space environment during its own operational period. For Electronics used for spacecraft control, there is a strict operation constraints for both ON and OFF procedure in order to inhibit the stress for converter (CV) used in electronics. There are two relays for electronics, the one is located in the input for CV, and the other is located in the ouput for CV. This paper proposed the protection circuit for sequential procedure using FET. Using the FET characteristics, abnormal activation of relay can be inhibited, and according to the worst case analysis, proposed circuit is performed its own protection circuit correctly.