• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.866-869
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• 2015

In this paper, we propose a device for detect front object using low-price the CW Doppler sensor to prevent safety accident such as a bicycle, an electric wheelchair users. For this propose, we develop a signal process board and the object motion detect algorithm using to analyzing output signal of the CW Doppler sensor. Output signal from CW Doppler sensor is analog I and analog Q. The CW Doppler sensor shows phase I and phase Q of object differently when the object approach, stop, drop by sensor. We develop an algorithm that can detect object by discrimination information of phase using the CW Doppler sensor. The verification use firmware of applied hardware and algorithm. Then, the motion information can be confirming output depending on motion object by experiment normally. As a result, we check that the sensing information output by following motion of object and confirm an algorithm and motion of signal processing board.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1175-1183
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• 2004

This paper propose a method to trace a moving object based on the information directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors involved in compressed video and then we calculate the amount of pan, tilt, zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. The moving object is designated initially by a user via bounding box. After then automatic tracking is performed based on the mean-shift algorithm of the motion flows of the object. The proposed method can improve the computation speed because the information is directly obtained from the MPEG-2 compressed video, but the object boundary is limited by blocks rather than pixels.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.161.5-161
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• 2001

Robots are required to assist our activities in daily life. In this paper, we focus on arm movement to catch moving object as one of important tasks frequently performed by human. We propose an algorithm which enables a robot to perform human-like arm motion to catch a moving object. First we analyze human hand trajectories and velocity profiles to catch an object. From the experimental results, we extract some characteristics in the process of approaching and following a moving object and confirm that these are necessary to realize human-like motion. We then adopt an instantaneous optimal control method which evaluates the error and energy cost at each sampling step, and design two time-varying weight matrices to introduce human characteristic into robot motion. The matrix concerning the error is defined as a time-increasing ...

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.15-22
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• 2005

This paper proposed a object tracking algorithm which can track contour of fast moving object through motion estimation. Since the proposed tracking algorithm is based on the radial representation, the motion estimation of object can be accomplished at the center of object with the low computation complexity. The motion estimation of object makes it possible to track object which move fast more than distance from center point to contour point for each frame. In addition, by introducing both gradient image and difference image into energy functions in the process of energy convergence, object tracking is more robust to the complex background. The results of experiment show that the proposed algorithm can track fast moving object in real-time and is robust under the complex background.

• 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.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.99-104
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• 2002

Existing methods of object tracking use template matching, re-detection of object boundaries or motion information. The template matching method requires very long computation time. The re-detection of object boundaries may produce false edges. The method using motion information shows poor tracking performance in moving camera. In this paper, a robust object tracking algorithm is proposed, using projected motion and histogram intersection. The initial object image is constructed by selecting the regions of interest after image segmentation. From the selected object, the approximate displacement of the object is computed by using 1-dimensional intensity projection in horizontal and vortical direction. Based on the estimated displacement, various template masks are constructed for possible orientations and scales of the object. The best template is selected by using the modified histogram intersection method. The robustness of the proposed tracking algorithm has been verified by experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.153.2-153
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• 2001

A technique is described for producing a virtual object with realistic motion. A 3-D human motion model is obtained by applying a developed motion capturing technique to a real human in motion. Factorization method is a technique for recovering 3-D shape of a rigid object from a single video image stream without using camera parameters. The technique is extended for recovering 3-D human motions. The proposed system is composed of three fixed cameras which take video images of a human motion. Three obtained image sequences are analyzed to yield measurement matrices at individual sampling times, and they are merged into a single measurement matrix to which the factorization is applied and the 3-D human motion is recovered ...

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1086-1092
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• 2009

Stereoscopic conversion has been an important and challenging issue for many 3-D video applications. Usually, there are two different stereoscopic conversion approaches, i.e., image motion-based conversion that uses motion information and object-based conversion that partitions an image into moving or static foreground object(s) and background and then converts the foreground in a stereoscopic object. As well, since the input sequence is MPEG-1/2 compressed video, motion data stored in compressed bitstream are often unreliable and thus the image motion-based conversion might fail. To solve this problem, we present the utilization of key-motion that has the better accuracy of estimated or extracted motion information. To deal with diverse motion types, a transform space produced from motion vectors and color differences is introduced. A key-motion is determined from the transform space and its associated stereoscopic image is generated. Experimental results validate effectiveness and robustness of the proposed method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.5
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• pp.552-567
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• 2017

The floating crane vessel in waves gives rise to the motion of the lifted object which is connected to the hoisting wire. The dynamic tension induced by the lifted object also affects the motion responses of the floating crane vessel in return. In this study, coupled motion responses of a floating crane vessel and a lifted subsea manifold during deep-water installation operations were investigated by both experiments and numerical calculations. A series of model tests for the deep-water lifting operation were performed at Ocean Engineering Basin of KRISO. For the model test, the vessel with a crane control system and a typical subsea manifold were examined. To validate the experimental results, a frequency-domain motion analysis method is applied. The coupled motion equations of the crane vessel and the lifted object are solved in the frequency domain with an additional linear stiffness matrix due to the hoisting wire. The hydrodynamic coefficients of the lifted object, which is a significant factor to affect the coupled dynamics, are estimated based on the perforation value of the structure and the CFD results. The discussions were made on three main points. First, the motion characteristics of the lifted object as well as the crane vessel were studied by comparing the calculation results. Second, the dynamic tension of the hoisting wire were evaluated under the various wave conditions. Final discussion was made on the effect of passive heave compensator on the motion and tension responses.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.27-34
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• 2004

This paper proposes a method to trace and interpret a moving object based on the information which can be directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors included in compressed video. We calculate the amount of pan, tilt, and zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. Initially, a moving object to be traced is designated by user via bounding box. After then automatic tracking Is performed based on the accumulated motion flows according to the area contributions. Also, in order to reduce the cumulative tracking error, the object area is reshaped in the first I-frame of a GOP by matching the DCT coefficients. The proposed method can improve the computation speed because the information can be directly obtained from the MPEG-2 compressed video, but the object boundary is limited by macro-blocks rather than pixels. Also, the proposed method is proper for approximate object tracking rather than accurate tracing of an object because of limited information available in the compressed video data.