• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.131-136
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• 2005

In 3D animation rendering process, Although we can render the output as a movie file format, most productions use image sequences in their rendering pipelines. This Image Sequence rendering process is extremely important step in final compositing in movie industries. Although there are various type of making image rendering processes, TGA format is one of most widely used bitmap file formats using in industries. People may ask TGA format is most suitable for in any case. As we know 3D softwares have their own image formats. so we need to testify on this. In this paper, we are going to focus on Alias' 3D package software called MAYA which we will analyze of compressing image sequence, Image quality, supporting Alpha channels in compositing, and Z-depth Information. The purpose of this paper is providing to 3D Pipeline as a guideline about effective image sequence format.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1491-1501
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• 2017

In this paper, we propose a method to measure respiration rate by dividing the respiration related region in depth image using level set method. In the conventional method, the respiration related region was separated using the pre-defined region designated by the user. We separate the respiration related region using level set method combining shape prior knowledge. Median filter and clipping are performed as a preprocessing method for noise reduction in the depth image. As a feasibility test, respiration activity was recorded using depth camera in various environments with arm movements or body movements during breathing. Respiration activity was also measured simultaneously using a chest belt to verify the accuracy of calculated respiration rate. Experimental results show that our proposed method shows good performance for respiration rate estimation in various situation compared with the conventional method.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.351-357
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• 2013

Two cameras which function like human eyes, are needed to make 3D stereoscopic image. That is, stereoscopic image is made via 3 dimensional image processing for combining two images from left and right camera. In this paper two high resolution zoom cameras are used to make HD resolution stereoscopic camera. And the algorithm which convert to stereoscopic image from HD resolution zoom camera image, is implemented using FPGA for real-time operation. The algorithm which measure the depth of object between left and right image is proposed.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.629-644
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• 2010

A real-time image georeferencing system requires all inputs to be determined in real-time. The intrinsic camera parameters can be identified in advance from a camera calibration process while other control information can be derived instantaneously from real-time GPS/INS data. The bottleneck process is tie point acquisition since manual operations will be definitely obstacles for real-time system while the existing extraction methods are not fast enough. In this paper, we present a fast-and-automated image matching technique based on the KLT tracker to obtain a set of tie-points in real-time. The proposed work accelerates the KLT tracker by supplying the initial guessed tie-points computed using the GPS/INS data. Originally, the KLT only works effectively when the displacement between tie-points is small. To drive an automated solution, this paper suggests an appropriate number of depth levels for multi-resolution tracking under large displacement using the knowledge of uncertainties the GPS/INS data measurements. The experimental results show that our suggested depth levels is promising and the proposed work can obtain tie-points faster than the ordinary KLT by 13% with no less accuracy. This promising result suggests that our proposed algorithm can be effectively integrated into the real-time image georeferencing for further developing a real-time surveillance application.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.95-101
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• 2008

In this paper, we present a new smoothing algorithm for variable depth mapping for real time stereoscopic image for 3D display. Proposed algorithm is based on the physical concept, called Laplacian equation and we also discuss the mapping of the depth from scene to displayed image. The approach to solve the problem in stereoscopic image which we adopt in this paper is similar to multi-region algorithm which was proposed by N.Holliman. The main difference thing in our algorithm compared with the N.Holliman's multi-region algorithm is that we use the Laplacian equation by considering the distance between viewer and object. We implement the real time stereoscopic image generation method for OpenGL on the circular polarized LCD screen to demonstrate its real functioning in the visual sensory system in human brain. Even though we make and use artificial objects by using OpenGL to simulate the proposed algorithm we assure that this technology may be applied to stereoscopic camera system not only for personal computer system but also for public broad cast system.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.818-828
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• 2014

After emerging of Microsoft Kinect, the interest in three-dimensional (3D) depth image was significantly increased. Depth image data of an object can be converted to 3D coordinates by simple arithmetic calculation and then can be reconstructed as a 3D model on computer. However, because the surface coordinates can be acquired only from the front area facing Kinect, total solid which has a closed surface cannot be reconstructed. In this paper, 3D registration method for multiple Kinects was suggested, in which surface information from each Kinect was simultaneously collected and registered in real time to build 3D total solid. To unify relative coordinate system used by each Kinect, 3D perspective transform was adopted. Also, to detect control points which are necessary to generate transformation matrix, 3D randomized Hough transform was used. Once transform matrices were generated, real time 3D reconstruction of various objects was possible. To verify the usefulness of suggested method, human arms were 3D reconstructed and the volumes of them were measured by using four Kinects. This volume measuring system was developed to monitor the level of lymphedema of patients after cancer treatment and the measurement difference with medical CT was lower than 5%, expected CT reconstruction error.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1690-1710
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• 2014

In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.643-650
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• 2014

A hardware implementation of phase calculator for extracting 3D depth image from TOF(Time-Of-Flight) sensor is described. The designed phase calculator adopts redundant binary number systems and a pipelined architecture to improve throughput and speed. It performs arctangent operation using vectoring mode of DCORDIC(Differential COordinate Rotation DIgital Computer) algorithm. Fixed-point MATLAB simulations are carried out to determine the optimal bit-widths and number of iteration. The phase calculator has ben verified by FPGA-in-the-loop verification using MATLAB/Simulink. A test chip has been fabricated using a TSMC $0.18-{\mu}m$ CMOS process, and test results show that the chip functions correctly. It has 82,000 gates and the estimated throughput is 400 MS/s at 400Mhz@1.8V.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2727-2732
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• 2014

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.