• Journal of Korea Multimedia Society
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• v.15 no.8
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• pp.963-976
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• 2012

'Gesture' except for voice is the most intuitive means of communication. Thus, many researches on how to control computer using gesture are in progress. User detection and tracking in these studies is one of the most important processes. Conventional 2D object detection and tracking methods are sensitive to changes in the environment or lights, and a mix of 2D and 3D information methods has the disadvantage of a lot of computational complexity. In addition, using conventional 3D information methods can not segment similar depth object. In this paper, we propose object detection and tracking method using Depth Projection Map that is the cumulative value of the depth and motion information. Simulation results show that our method is robust to changes in lighting or environment, and has faster operation speed, and can work well for detection and tracking of similar depth objects.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.2066-2067
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• 2009

1차년도에는 햅틱 시나리오의 비주얼 쓰레드로서의 환경을 구축하여 햅틱 렌더링과 그래픽 렌더링의 연동을 위한 연구를 수행하였고 햅틱 장비로부터 오는 다양한 데이터 처리를 위한 데이터 로딩 기법을 연구하고 이를 멀티 코어 CPU를 이용하여 단일 조명상에서 광선 추적하는 알고리즘을 개발하였다. 당해연도에는 1Khz 의 속도를 가진 햅틱 렌더링과의 불연속성을 해결하기 위하여 GPU를 이용한 보다 빠른 고품질의 광선 추적 알고리즘을 개발하고자 한다. 이를 위하여 NVIDIA의 범용 솔루션인 CUDA를 통해 병렬 처리를 통해 실시간으로 다중 광원을 가진 Dynamic한 장면을 갱신할 수 있도록 한다. 또한 심장, 폐, 간과 같은 반투명한 재질을 가진 신체 장기 표현을 위해 각 재질에 맞는 양방향의 표면 내부 산란 분포함수를 간략화하여 차후 년도의 연구에 반영한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.329-334
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• 2011

This paper presents the method for location estimation with obstacle tracking method. A laser scanner is used to implement the system, and we assume that the map information is known. We matches the measurement of the laser scanner to estimate the location of the robot by using sequential monte carlo (SMC) method. After estimating the robot's location, the pose of obstacles are detected and tracked, hence, we can predict the collision risk of them. Finally, we present the experiment results to verify the proposed method.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.1
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• pp.53-59
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• 2014

In multiple object tracking, accurate detection for each of objects that appear sequentially and effective tracking in complicated cases that they are overlapped with each other are very important. In this paper, we propose a multiple object tracking system that has a concrete detection and tracking characteristics by using multi-lateral histogram and SIFT feature extraction algorithm. Especially, by limiting the matching area to object's inside and by utilizing the location informations in the keypoint matching process of SIFT algorithm, we advanced the tracking performance for multiple objects. Based on the experimental results, we found that the proposed tracking system has a robust tracking operation in the complicated environments that multiple objects are frequently overlapped in various of directions.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.453-458
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• 2013

Aside from the issues like energy saving and maximizing network lifetime. WMSN has another issue to deal with: support of quality of service(QoS) which is required especially for handling real-time data such as object tracking and data gathering. This paper proposes a multipath routing algorithm considering the distance to sink node, energy level and link quality of neighbour nodes. Proposed algorithm supports multipath routing path with high quality links. Hence it helps to reduce a power consumption concentration that happens in particular set of nodes along the frequently selected route. It also specifies a service quality pattern and a service quality level depending on traffic pattern. By doing this, the proposed algorithm can realize a differentiated service with QoS guaranteed data transmission.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.150-157
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• 2015

Pedestrian detection has largely been researched as one of the important technologies for autonomous driving vehicle and preventing accidents. There are two categories for pedestrian detection, camera-based and LIDAR-based. LIDAR-based methods have the advantage of the wide angle of view and insensitivity of illuminance change while camera-based methods have not. However, there are several problems with 3D LIDAR, such as insufficient resolution to detect distant pedestrians and decrease in detection rate in a complex situation due to segmentation error and occlusion. In this paper, two methods using GM-PHD filter are proposed to improve the poor rates of pedestrian detection algorithms based on 3D LIDAR. First one improves detection performance and resolution of object by automatic accumulation of points in previous frames onto current objects. Second one additionally enhances the detection results by applying the GM-PHD filter which is modified in order to handle the poor situation to classified multi target. A quantitative evaluation with autonomously acquired road environment data shows the proposed methods highly increase the performance of existing pedestrian detection algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.187-192
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• 2008

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human Jollowing by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2179-2184
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper described appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.780-785
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• 2010

This paper introduces GP(Genetic Programming) based color detection model for an object detection and tracking. Existing color detection methods have used linear/nonlinear transformatin of RGB color-model and improved color model for illumination variation by optimization or learning techniques. However, most of cases have difficulties to classify various of colors because of interference of among color channels and are not robust for illumination variation. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various colors and images with different lighting conditions.