• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.73-85
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• 1995

The sensor system to measure the distance precisely from the center of the sensor system to the obstacle is needed to recognize the surrounding environments, and the sensor system is to be calibrated thoroughly to get the range information exactly. This study covers the calibration of the active range sensor which consists of camera and laser slit emitting device, and provides the equations to get the 3D range data. This can be possible by obtaining the extrinsic parameters of laser slit emitting device through image processing the slits measured during the constant distance intervals and the intrinsic parameters from the calibration of camera. The 3D range data equation derived from the simple geometric assumptions is proved to be applicable to the general cases using the calibration parameters. Also the exact 3D range data were obtained to the object from the real experiment.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.27-33
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• 2016

In this study we propose a method for 3D landform reconstruction and object modeling method by generating contour lines on the map using a depth sensor which abstracts characteristics of geological layers from the depth map. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust contour and object can be extracted. The algorithm suggested in this paper first abstracts the characteristics of each geological layer from the depth map image and rearranges it into the proper order, then creates contour lines using the Bezier curve. Using the created contour lines, 3D images are reconstructed through rendering by mapping RGB images of the visual camera. Experimental results show that the proposed method using depth sensor can reconstruct contour map and 3D modeling in real-time. The generation of the contours with depth data is more efficient and economical in terms of the quality and accuracy.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.585-588
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• 2015

The technical challenge of 3D image display using the wireless sensor were applied to variable areas and scopes. This techniques need to very accurate location and speed informations and recognitions to moving objects. The tracking challenges of the moving objects location that combined 3D location and speed sensor were applied to sports and healthcare areas. This areas seek to the accuracy and collections and tightly related to image display and analysis techniques. In this paper, We developed the 3D motion display that can be monitor moving objects on the 3D virtual space. For this works, we constructed the database that collected informations through 9-axis sensor and demonstrated the result of 3D motion display on the Window based environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.126-148
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• 2015

Different from the existing works on coverage problems in wireless sensor networks (WSNs), this paper considers the exposure-path prevention problem by using the percolation theory in three dimensional (3D) WSNs, which can be implemented in intruder detecting applications. In this paper, to avoid the loose bounds of critical density, a bond percolation-based scheme is proposed to put the exposure-path problem into a 3D uniform lattice. Within this scheme, the tighter bonds of critical density for omnidirectional and directional sensor networks under random sensor deployment-a 3D Poisson process are derived. Extensive simulation results show that our scheme generates tighter bounds of critical density with no exposure path in 3D WSNs.

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.279-285
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• 2022

Recently, 3D printing technology has gained increased attention in the manufacturing industry because it allows the manufacturing of complex but sophisticated structures as well as moderate production speed. Owing to advantages of 3D printers, such as flexible design, customization, rapid prototyping, and ease of access, can also be advantageous to sensor developments, 3D printing demands have increased in various active device fields, including sensor manufacturing. In particular, 3D printing technology is of significant interest in tactile sensor development where piezoelectric materials are typically embedded to acquire voltage signals from external stimuli. In regard with piezoelectricity, researchers have worked with various piezoelectric materials to achieve high piezoelectric response, but the structural approach is limited because ceramics have been regarded as challenging materials for complex design owing to their limited manufacturing methods. If appropriate piezoelectric materials and approaches to design are used, sensors can be fabricated with the improved piezoelectric response and high sensitivity that cannot be found in common bulk materials. In this study, various 3D printing technologies, material combinations, and applications of various piezoelectric sensors using the 3D printing method are reviewed.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.189-194
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• 2016

Recently, there is increasing demand for image processing technology while activated the use of equipments such as camera, camcorder and CCTV. In particular, research and development related to 3D image technology using the depth camera such as Kinect sensor has been more activated. Kinect sensor is a high-performance camera that can acquire a 3D human skeleton structure via a RGB, skeleton and depth image in real-time frame-by-frame. In this paper, we develop a system. This system captures the motion of a 3D human skeleton structure using the Kinect sensor. And this system can be stored by selecting the motion file format as trc and bvh that is used for general purposes. The system also has a function that converts TRC motion captured format file into BVH format. Finally, this paper confirms visually through the motion capture data viewer that motion data captured using the Kinect sensor is captured correctly.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1657-1666
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• 2010

Underwater wireless sensor networks (UWSN) need stable efficient data transmission methods because of environmental characteristics such as limited energy resource, limited communication bandwidth, variable propagation delay and so on. In this paper, we explain an enhanced hybrid transmission method that uses a hexagon tessellation with an ideal cell size in a two-dimensional underwater wireless sensor network model (2D) that consists of fixed position sensors on the bottom of the ocean. We also propose an energy efficient sensing and communication coverage method for effective data transmission in a three-dimensional underwater wireless sensor network model (3D) that equips anchored sensors on the bottom of the ocean. Our simulation results show that proposed methods are more energy efficient than the existing methods for each model.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.156-165
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• 2005

Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.

• Journal of Industrial Technology
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• v.19
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• pp.173-178
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• 1999

In many areas of technology there are machines and systems controllable in up to six degrees of freedom. Helicopters and underwater vehicles, industrial robots are among the first representatives of this category. They need six degrees of freedom in order to move and orient within their workspace. An even broader and more explosively growing area is 3D computer graphics and virtual environment. In this work, functions of 3D input device are described and two types of commercial 3D input device are presented. Then, a preliminary experiment of a low cost 6 axis force/moment sensor is presented that can also be sued as a 3D input device. A low cost force/moment sensor and its application in robot teaching experiment is described. It computes the direction of 3 components of the force and 3 components of the moment applied by human holding the sensor by hand. The concept is shown by an experiment where the tool position and orientation of a robot in 3 dimensional space is controlled by the proposed sensor.