• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.916-924
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• 2014

It is possible to improve the accuracy of the motion estimation for a video by applying a variable block size. However, it has limits in the zoom motion estimation. In this paper, we propose a method for estimating the zoom motion with variable block size. The proposed method separates the background within the object picture by depth information obtained from a depth camera, and only the object regions are applied to zoom scale, but the background is not applied. In addition, the object regions select efficiently variable block size mode in consideration of the generated motion vectors and the accuracy of motion estimation at the same time. Simulation results show the accuracy of the motion estimation and the number of motion vectors for the proposed method. It is verified that the proposed method can reduce the number of motion while maintaining the similar accuracy of motion estimation than the conventional motion estimation methods.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.44-53
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• 2011

In this paper, we propose a 3D conversion algorithm of 2D video using depth layer partition method. In the proposed algorithm, we first set frame groups using cut detection algorithm. Each divided frame groups will reduce the possibility of error propagation in the process of motion estimation. Depth image generation is the core technique in 2D/3D conversion algorithm. Therefore, we use two depth map generation algorithms. In the first, segmentation and motion information are used, and in the other, edge directional histogram is used. After applying depth layer partition algorithm which separates objects(foreground) and the background from the original image, the extracted two depth maps are properly merged. Through experiments, we verify that the proposed algorithm generates reliable depth map and good conversion results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1805-1810
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• 2015

Increasing of depth data accessibility, depth data is used in many researches. Motion recognition of computer vision also widely use depth image. More accuracy motion recognition system needs more stable depth data. But depth sensor has a noise. This noise affect accuracy of the motion recognition system, we should noise suppression. In this paper, we propose using spatial domain and temporal domain stabilization for depth image and makes it hardware IP. We adapted our hardware to floor removing algorithm and verification its effect. we did realtime verification using FPGA and APU. Designed hardware has maximum frequency 202.184MHz.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.676-683
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• 2012

Motion estimation in video coding greatly affects implementation complexity. In this paper, a reducing method of the complexity in motion estimation is proposed by using both the depth and color cameras. We obtain object information with video sequence from distance information calculated by depth camera, then perform labeling for grouping pixels within similar distances as the same object. Three search regions (background, inside-object, boundary) are determined adaptively for each of motion estimation blocks within current and reference pictures. If a current block is the inside-object region, then motion is searched within the inside-object region of reference picture. Also if a current block is the background region, then motion is searched within the background region of reference picture. From simulation results, we can see that the proposed method compared to the full search method remains the almost same as the motion estimated difference signal and significantly reduces the searching complexity.

• Bulletin of the Society of Naval Architects of Korea
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• v.19 no.1
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• pp.23-32
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• 1982

Herein the motion of a freely-floating sphere in a water of finite depth is analysed within the framework of a linear potential theory. A velocity potential describing fluid motion is generated by distributing pulsating sources and dipoles on the immersed surface of the sphere, without introducing an inner flow model. The potential becomes the solution of an integral equation of Fredholm's second type. In the light of the vertical axisymmetry of the flow, surface integrals reduce to line integrals, which are approximated by summation of the products of the integrand and the length of segments along the contour. Following this computational scheme the diffraction potential and the radiation potential are determined from the same algorithm of solving a set of simultaneous linear equations. Upon knowing values of the potentials hydrodynamic forces such as added mass, hydrodynamic damping and wave exciting forces are evaluated by the integrating pressure over the immersed surface of the sphere. It is found in the case of finite water depth that the hydrodynamic forces are much different from the corresponding ones in deep water. Accordingly motion response of the sphere in a water of finite depth displays a particular behavior both in a amplitude and phase.

• Bulletin of the Society of Naval Architects of Korea
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• v.20 no.4
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• pp.33-40
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• 1983

The drift force acting on a freely-floating sphere in water of finite depth is studied within the framework of a linear potential theory. A velocity potential describing fluid motion is determined by distribution pulsating sources and dipoles on the immersed surface of the sphere. Upon knowing values of the potential, hydrodynamic forces are evaluated by integrating pressures over the immersed surface of the sphere. The motion response of the sphere in water of finite depth is obtained by solving the equation of motion. From these results, the drift force on the sphere is evaluated by the momentum theorem, in which a far-field velocity potential is utilized in forms of Kochin function. The drift force coefficient Cdr of a fixed sphere increases monotononically with non-dimensional wave frequency ${\sigma}a$. On the other hand, in freely-floating case, the Cdr has a peak value at ${\sigma}a$ of heave resonance. The magnitude of the drift force coefficient Cdr in the case of finite depth is different form that for deep water, but the general tendency seems to be similar in both cases. It is to note that Cdr is greater than 1.0 when non-dimensional water depth d/a is 1.5 in the case of freely-floating sphere.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12C
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• pp.1147-1153
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• 2009

We propose a novel image segmentation and segment-based stereo matching technique using color, depth, and motion information. Proposed technique firstly splits reference images into foreground region or background region using depth information from depth camera. Then each region is segmented into small segments with color information. Moreover, extracted segments in current frame are tracked in the next frame in order to maintain depth consistency between frames. The initial depth from the depth camera is also used to set the depth search range for stereo matching. Proposed segment-based stereo matching technique was compared with conventional one without foreground and background separation and other conventional one without motion tracking of segments. Simulation results showed that the improvement of segment extraction and depth estimation consistencies by proposed technique compared to conventional ones especially at the static background region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1103-1109
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• 2014

The motion recognition system has been broadly studied in digital image and video processing fields. Recently, method using th depth image is used very useful. However, recognition accuracy of depth image based method will be loss caused by size and shape of object distorted for angle of the depth sensor. Therefore, distortion correction of depth sensor is positively necessary for distinguished performance of the recognition system. In this paper, we propose a pre-processing algorithm to improve the motion recognition system. Depth data from depth sensor converted to real world, performed the corrected angle, and then inverse converted to projective world. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1627-1633
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• 2017

Human dance is difficult to learn since there is no effective way to imitate an expert's motion, a sequence of complicated body movements, without taking an actual class. In this paper, we propose a dance learning system using human depth information. In the proposed system, a set of example motions are captured from various expert dancers through a marker-free motion capture and archived into a motion database server for online dance lessons. Given the end-user devices such as tablet and kiosk PCs, a student can learn a desired motion selected from the database and send one's own motion to an instructor for online feedback. During this learning process, our system provides a posture-based motion search and multi-mode views to support the efficient exchange of motion data between the student and instructor under a networked environment. The experimental results demonstrate that our system is capable to improve the student's dance skills over a given period of time.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.180-187
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• 2006

This paper presents a new sensor system, CALOS, for motion estimation and 3D reconstruction. The 2D laser sensor provides accurate depth information of a plane, not the whole 3D structure. On the contrary, the CCD cameras provide the projected image of whole 3D scene, not the depth of the scene. To overcome the limitations, we combine these two types of sensors, the laser sensor and the CCD cameras. We develop a motion estimation scheme appropriate for this sensor system. In the proposed scheme, the motion between two frames is estimated by using three points among the scan data and their corresponding image points, and refined by non-linear optimization. We validate the accuracy of the proposed method by 3D reconstruction using real images. The results show that the proposed system can be a practical solution for motion estimation as well as for 3D reconstruction.