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Human Action Recognition Using Ordinal Measure of Accumulated Motion
Kim, Wonjun,Lee, Jaeho,Kim, Minjin,Oh, Daeyoung,Kim, Changick Hindawi Publishing Corporation 2010 EURASIP journal on advances in signal processing Vol.2010 No.1
<P>This paper presents a method for recognizing human actions from a single query action video. We propose an action recognition scheme based on the ordinal measure of accumulated motion, which is robust to variations of appearances. To this end, we first define the accumulated motion image (AMI) using image differences. Then the AMI of the query action video is resized to a N×N subimage by intensity averaging and a rank matrix is generated by ordering the sample values in the sub-image. By computing the distances from the rank matrix of the query action video to the rank matrices of all local windows in the target video, local windows close to the query action are detected as candidates. To find the best match among the candidates, their energy histograms, which are obtained by projecting AMI values in horizontal and vertical directions, respectively, are compared with those of the query action video. The proposed method does not require any preprocessing task such as learning and segmentation. To justify the efficiency and robustness of our approach, the experiments are conducted on various datasets.</P>
이동형 단말기에서의 축구경기 시청을 위한 해상도 및 관심 영역 크기에 관한 사용자 만족도 조사
김창익(Changick Kim),고재승(Jaeseung Ko),안일구(Ilkoo Ahn),이재호(Jaeho Lee),서기원(Kiwon Seo),권재훈(Jae Hoon Kwon),주영훈(Young Hun Joo),오윤제(Yun Je Oh) 한국방송·미디어공학회 2006 방송공학회논문지 Vol.11 No.3
The recent advances in multimedia signal coding and transmission technologies allow lots of users to watch videos on small LCD displays. In this paper, we briefly describe an intelligent display technique to provide small-display-viewers with comfortable experiences, and study the minimum image size tolerated and utility of displaying region of interest (ROI) only when needed. The study, with 111 participants, examines minimum image size to ensure viewers pleasant viewing experiences, and evaluates the degree of satisfaction when they are viewed with region of interest (ROI) only. The experimental results show that the ROI display enhances the viewers’ satisfaction when the image size becomes less than 320X240, and thus it is useful to provide the intelligent display, if necessary, which can extract and display ROI only.
멀티미디어 단말기 사용자를 위한 축구 경기 비디오의 점수상자 추출
김원준(Kim Won-Jun),김창익(Kim Changick) 한국방송·미디어공학회 2006 한국방송공학회 학술발표대회 논문집 Vol.2006 No.-
최근 정보통신 기술의 급속한 발전으로 소형 이동형 단말기를 이용한 각종 스포츠 경기 시청이 두드러지게 증가하고 있다. 그럼에도 불구하고 이동형 단말기를 통해 제공되는 영상은 일반 TV나 HDTV용으로 제작되어 소형 이동형 단말기의 사용자가 화면을 통해 스포츠 경기의 상황을 인식하는데 많은 불편함을 주고 있다. 특히, 경기 진행 시간이나 점수를 포함하는 점수상자(scoreboard)는 경기의 상황을 파악하는데 매우 중요한 역할을 하나, 소형 이동형 단말기의 작은 화면에서는 점수상자의 내용을 정확히 인식하기가 쉽지 않다. 이에 본 논문은 많은 사람들이 즐겨보는 축구 경기에 대하여 짧은 학습 기간을 갖는 효율적인 점수상자 추출 방법을 제안하고자 한다. 제안하는 알고리즘은 점수상자와 주변 환경의 밝기 정보를 이용한 점수상자 경계 좌표 추출, 학습을 통한 최적의 경계 좌표 결정, 점수상자 영역 추출 및 확대의 세 단계로 구성된다. 제안하는 알고리즘은 점수상자가 없는 프레임에서도 몇 프레임 앞서 표시된 점수상자의 저장을 통해 디스플레이가 가능하도록 하였다. 다양한 축구경기 비디오에 대한 실험을 통해 제안된 알고리즘이 소형 이동형 단말기 상에서 점수상자를 추출하고 이를 사용자가 쉽게 인식할 수 있도록 확대하여 디스플레이 하는 좋은 해결책임을 보이고자 한다.
A Texture-Aware Salient Edge Model for Image Retargeting
Wonjun Kim,Changick Kim IEEE 2011 IEEE signal processing letters Vol.18 No.11
<P>Image retargeting aims at adapting a given image to fit the size of arbitrary displays without severe visual distortions. To achieve this task successfully, it is essential to define a reliable image importance map (IIM) since it guides subsequent retargeting procedures. In this letter, we introduce a novel IIM for effective image retargeting. Specifically, we define our IIM by exploiting the higher order statistics (HOS) of the diffusion space for image retargeting. We call it texture-aware salient edge (TASE) map. Based on the proposed TASE map, we obtain visually acceptable retargeting results, even in the cluttered background and in the presence of noise as well. The proposed method has been extensively tested, and experimental results show that the proposed scheme is effective for image retargeting compared to other various state-of-the-art methods.</P>
Contrast Enhancement Using Combined 1-D and 2-D Histogram-Based Techniques
Daeyeong Kim,Changick Kim IEEE Signal Processing Society 2017 IEEE signal processing letters Vol.24 No.6
<P>This letter presents an adaptive contrast enhancement algorithm considering both preservation of the shape of a one-dimensional (1-D) histogram and statistical information on the gray-level differences between neighboring pixels obtained by a 2-D histogram. The proposed system consists of two modules. One is to enhance the entire contrast by stretching the 1-D histogram while preserving the shape of the histogram. The other is to improve the details of nonsmooth areas occurring frequently in input images. These are formulated into a single constrained optimization problem. Compared with several state-of-the-art enhancement algorithms, the proposed algorithm shows highly competitive performance.</P>
Spatiotemporal Saliency Detection and Its Applications in Static and Dynamic Scenes
Wonjun Kim,Chanho Jung,Changick Kim IEEE 2011 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDE Vol.21 No.4
<P>This paper presents a novel method for detecting salient regions in both images and videos based on a discriminant center-surround hypothesis that the salient region stands out from its surroundings. To this end, our spatiotemporal approach combines the spatial saliency by computing distances between ordinal signatures of edge and color orientations obtained from the center and the surrounding regions and the temporal saliency by simply computing the sum of absolute difference between temporal gradients of the center and the surrounding regions. Our proposed method is computationally efficient, reliable, and simple to implement and thus it can be easily extended to various applications such as image retargeting and moving object extraction. The proposed method has been extensively tested and the results show that the proposed scheme is effective in detecting saliency compared to various state-of-the-art methods.</P>
Spatiotemporal Saliency Detection Using Textural Contrast and Its Applications
Wonjun Kim,Changick Kim IEEE 2014 IEEE transactions on circuits and systems for vide Vol.24 No.4
<P>Saliency detection has been extensively studied due to its promising contributions for various computer vision applications. However, most existing methods are easily biased toward edges or corners, which are statistically significant, but not necessarily relevant. Moreover, they often fail to find salient regions in complex scenes due to ambiguities between salient regions and highly textured backgrounds. In this paper, we present a novel unified framework for spatiotemporal saliency detection based on textural contrast. Our method is simple and robust, yet biologically plausible; thus, it can be easily extended to various applications, such as image retargeting, object segmentation, and video surveillance. Based on various datasets, we conduct comparative evaluations of 12 representative saliency detection models presented in the literature, and the results show that the proposed scheme outperforms other previously developed methods in detecting salient regions of the static and dynamic scenes.</P>