• Journal of IKEEE
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• v.25 no.1
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• pp.83-87
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• 2021

In harsh environments such as fog or fine dust, the cameras' detection ability for object recognition may significantly decrease. In order to accurately obtain important information even in bad weather, fog removal algorithms are necessarily required. Research has been conducted in various ways, such as computer vision/data-based fog removal technology. In those techniques, estimating the amount of fog through the input image's depth information is an important procedure. In this paper, a linear model is presented under the assumption that the image dark channel dictionary, saturation ∗ value, and sharpness characteristics are linearly related to depth information. The proposed method of haze removal through a linear model shows the superiority of algorithm performance in quantitative numerical evaluation.

• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.410-414
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• 2013

In this paper, we propose a 3D display method combining a pickup process using axially recorded multiple images and an integral imaging display process. First, we extract the color and depth information of 3D objects for displaying 3D images from axially recorded multiple 2D images. Next, using the extracted depth map and color images, elemental images are computationally synthesized based on a ray mapping model between 3D space and an elemental image plane. Finally, we display 3D images optically by an integral imaging system with a lenslet array. To show the usefulness of the proposed system, we carry out optical experiments for 3D objects and present the experimental results.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.79-82
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• 2012

3차원 멀티미디어 서비스에 대한 관심이 높아짐에 따라 관련 연구들이 현재 다양하게 논의되고 있다. Stereoscopy영상을 생성하기 위한 기존의 방법으로는 두 대의 촬영용 카메라를 일정한 간격으로 띄워놓고 피사체를 촬영한 후 해당 좌시점과 우시점을 생성하는 방법을 이용하였다. 하지만 이는 영상 대역폭의 부담을 가져오게 된다. 이를 해결하기 위하여 Depth정보와 한 장의 영상을 이용한 DIBR(Depth Image Based Rendering) Algorithm에 대한 연구가 많이 이루어지고 있다. 그중 Gaussian Depth Map을 이용한 Hole-Filling 방법은 DIBR에서 가장 자연스러운 결과를 보여주지만 다른 DIBR Algorithm들에 비해 속도가 현저히 느리다는 단점이 있다. 본 논문에서는 영상 생성의 고속화를 위해 GPU를 이용한 Gaussian Hole-Filling Algorithm의 병렬처리 구조를 제안하고 이를 이용한 DIBR Algorithm 생성과정을 제시한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1283-1288
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• 2009

In general, a 3D computer graphic model is being used to generate a digital hologram as theinput information because the 3D information of an object can be extracted from a 3D model, easily. The 3D information of a real scene can be extracted by using a depth camera. The 3D information, point cloud, corresponding to real scene is extracted from a taken image pair, a gray texture and a depth map, by a depth camera. The extracted point cloud is used to generate a digital hologram as input information. The digital hologram is generated by using the coherent holographic stereogram, which is a fast digital hologram generation algorithm based on segmentation. The generated digital hologram using the taken image pair by a depth camera is reconstructed by the Fresnel approximation. By this method, the digital hologram corresponding to a real scene or a real object could be generated by using the fast digital hologram generation algorithm. Furthermore, experimental results are satisfactory.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.53-66
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• 2006

Recent technique has shown high interest in 3D stereoscopic image, one out of high immersion appearance techniques. Unlike general 2D image, 3D stereoscopic image is generated by 3D geometric information. Therefore, the lack of 3D geometric information sometimes imposes restrictions or makes editing more tedious. We propose a new unsupervised technique aimed to generate stereoscopic image which is estimated by depth-map information using image-based modeling from a single input image. The proposed system is implemented as the Adobe Photoshop(R) plug-in for considering generality and expandability, and also supports a preview function of interactive 3D stereoscopic image to determine stereoscopic view of high quality.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1927-1935
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• 2016

This paper propose a framework for human body parts in RGB-D image. We conduct tasks of obtaining person area, finding candidate areas and local detection in order to detect hand, foot and head which have features of long accumulative geodesic distance. A person area is obtained with background subtraction and noise removal by using depth image which is robust to illumination change. Finding candidate areas performs construction of graph model which allows us to measure accumulative geodesic distance for the candidates. Instead of raw depth map, our approach constructs graph model with segmented regions by quadtree structure to improve searching time for the candidates. Local detection uses HOG based SVM for each parts, and head is detected for the first time. To minimize false detections for hand and foot parts, the candidates are classified with upper or lower body using the head position and properties of geodesic distance. Then, detect hand and foot with the local detectors. We evaluate our algorithm with datasets collected Kinect v2 sensor, and our approach shows good performance for head, hand and foot detection.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.163-172
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• 2010

The free viewpoint video delivers an active contents where users can see the images rendered from the viewpoints chosen by them. Its applications are found in broad areas, especially museum tour, entertainment and so forth. As a new free-viewpoint application, this paper presents a stereoscopic free-viewpoint TIP (Tour Into Picture) where users can navigate the inside of a single image controlling a virtual camera and utilizing depth data. Unlike conventional TIP methods providing 2D image or video, our proposed method can provide users with 3D stereoscopic and free-viewpoint contents. Navigating a picture with stereoscopic viewing can deliver more realistic and immersive perception. The method uses semi-automatic processing to make foreground mask, background image, and depth map. The second step is to navigate the single picture and to obtain rendered images by perspective projection. For the free-viewpoint viewing, a virtual camera whose operations include translation, rotation, look-around, and zooming is operated. In experiments, the proposed method was tested eth 'Danopungjun' that is one of famous paintings made in Chosun Dynasty. The free-viewpoint software is developed based on MFC Visual C++ and OpenGL libraries.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.286-289
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• 2012

본 논문은 3차원 깊이 정보를 이용하여 감시카메라에서 움직이는 사람을 검출하고 추적하는 방법을 제안한다. 제안하는 방법은 GMM(Gaussian mixture model)을 이용하여 배경과 움직이는 사람을 분리한 후, 분리된 영역을 CCL(connected-component labeling)을 통하여 각각 블랍(blob) 단위로 나누고 그 블랍을 추적한다. 그 중 블랍 단위로 나누는 데 있어 두 블랍이 합쳐진 경우, 3차원 깊이 정보를 이용하여 두 블랍을 분리하는 방법을 제안한다. 실험을 통하여 제안하는 방법의 결과를 보인다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.500-503
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• 1997

In this paper, a method for recognizing 3-D objects using the 3-D Hough transform and the robust stereo vision is studied. A 3-D object is recognized through two steps; modeling step and matching step. In modeling step, features of the object are extracted by analyzing the IGES file. In matching step, the values of the sensed image are compared with those of the IGES file which is assumed to location and orientation in the 3-D Hough transform domain. Since we use the 3-D Hough transform domain of the input image directly, the sensitivity to the noise and the high computational complexity could be significantly allcv~ated. Also, the cost efficiency is improved using the robust stereo vision for obtaining depth map image which is needed for 3-D Hough transform. In order lo verify the proposed method, real telephone model is recognized. Thc results of the location and orientation of the model are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.728-741
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• 2015

Stereo vision has become an important technical issue in the field of 3D imaging, machine vision, robotics, image analysis, and so on. The depth map extraction from stereo video is a key technology of stereoscopic 3D video requiring stereo correspondence algorithms. This is the matching process of the similarity measure for each disparity value, followed by an aggregation and optimization step. Since it requires a lot of computational power, there are significant speed-performance advantages when exploiting parallel processing available on processors. In this situation, multi-core CPU may allow many parallel programming technologies to be realized in users computing devices. This paper proposes parallel implementations for calculating disparity map using a shared memory programming and exploiting the streaming SIMD extension technology. By doing so, we can take advantage both of the hardware and software features of multi-core processor. For the performance evaluation, we implemented a parallel SAD algorithm with OpenMP and SSE2. Their processing speeds are compared with non parallel version on stereoscopic streaming video. The experimental results show that both technologies have a significant effect on the performance and achieve great improvements on processing speed.