• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.43-51
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• 2016

This paper presents the concept of "interactive teleprompter", which provides the user with interaction with oneself or other users for live television broadcasts or smart mirrors. In such interactive applications, eye contacts between the user and the regenerated image or between the user and other persons are important in handling psychological processes or non-verbal communications. Unfortunately, it is not straightforward to address the eye contact issues with conventional combination of normal display and video camera. To address this problem, we propose an "interactive" teleprompter enhanced from conventional teleprompter devices. Our interactive teleprompter can recognize the user's gestures by applying infra-red (IR) depth sensor. This paper also presents test results for a beam splitter which plays a critical role for teleprompter and is designed to handle both visual light for RGB camera and IR for Depth sensor effectively.

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.123-127
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• 2020

In this paper, the estimation of the disparity for depth extraction in monochrome complementary metal-oxide-semiconductor (CMOS) image sensors with offset pixel apertures is presented. To obtain the depth information, the disparity information between two different channel data of the offset pixel apertures is required. The disparity is caused by the difference in the response angle between the left- and right-offset pixel aperture images. A depth map is implemented by the generated disparity. Therefore, the disparity is the most important factor for realizing 3D images from the designed CMOS image sensor with offset pixel apertures. The disparity is influenced by the pixel height and offset value of the offset pixel aperture. To confirm this correlation, the offset value is set to maximum within the pixel area, and the disparity values corresponding to the difference in the heights are calculated and compared. The disparity is derived using the camera-lens formula. Two monochrome CMOS image sensors with offset pixel apertures are used in the disparity estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2400-2405
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• 2013

We detect the obstacle for the UGV(unmanned ground vehicle) from the compound image which is generated by stereo vision sensor masking the depth image and color image. Stereo vision sensor can gathers the distance information by stereo camera. The obstacle information from the depth compound image can be send to mobile robot and the robot can localize the indoor area. And, we test the performance of the mobile robot in terms of distance between the obstacle and the robot's position and also test the color, depth and compound image respectively. Moreover, we test the performance in terms of number of frame per second which is processed by operating machine. From the result, compound image shows the improved performance in distance and number of frames.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.437-446
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• 2012

A face detection algorithms using two-dimensional (2-D) intensity or color images have been studied for decades. Recently, with the development of low-cost range sensor, three-dimensional (3-D) information (i.e., depth image that represents the distance between a camera and objects) can be easily used to reliably extract facial features. Most people have a similar pattern of 3-D facial structure. This paper proposes a face detection method using intensity and depth images. At first, adaboost algorithm using intensity image classifies face and nonface candidate regions. Each candidate region is divided into $5{\times}5$ blocks and depth values are averaged in each block. Then, $5{\times}5$ block rank pattern is constructed by sorting block averages of depth values. Finally, candidate regions are classified as face and nonface regions by matching the constructed depth map based block rank patterns and a template pattern that is generated from training data set. For template matching, the $5{\times}5$ template block rank pattern is prior constructed by averaging block ranks using training data set. The proposed algorithm is tested on real images obtained by Kinect range sensor. Experimental results show that the proposed algorithm effectively eliminates most false positives with true positives well preserved.

• 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 Engineering Education Research
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• v.19 no.6
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• pp.49-56
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• 2016

The Human Robot Interface (HRI) based on 3D depth sensor on the docent robot is developed and the localization algorithm based on extended Kalman Filter (EKFLA) are proposed through the capstone design by graduate students in this paper. In addition to this, the performance of the proposed EKFLA is also analyzed. The developed HRI system consists of the route generation and localization algorithm, the user behavior pattern awareness algorithm, the map data generation and building algorithm, the obstacle detection and avoidance algorithm on the robot control modules that control the entire behaviors of the robot. It is confirmed that the improvement ratio of the localization error in EKFLA on the scenarios 1-3 is increased compared with the localization algorithm based on Kalman Filter (KFLA) as 21.96%, 25.81% and 15.03%, respectively.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.274-278
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• 2000

Ball end milling process is widely used in the die and mould manufacturing because of suitableness for the machining of free form surface. But, as ball end mill is long and thin, it is easily deflected by cutting force. In this study, Cutting force, tool deflection and surface precision was measured according to the change of depth and cutting location. Cutting force was acquired with tool dynamometer and a couple of eddy-current sensor measured tool deflection in x-y direction each. After machining, surface precision was measured with roundness tester and coordination measuring machine for sculptured surface angle change and cutting depth.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.4
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• pp.187-191
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• 2012

In these days, there are huge increases of concerning underwater acoustic sensor networks (UWASNs) to explore marine resources and to monitor climate change. To collect information from sensor nodes which are randomly deployed in underwater, Multi-Dimensional Scaling (MDS) based locating methods have been recently introduced, which consider sound speed to be constant in underwater. However, underwater sound speed tends to vary depending on underwater environment factors, such as depth, temperature, and salinity. In this paper, we propose a method considering environment factors, can influence upon sound speed in underwater, and introduce experimental setup which can follow up environmental factors.

• Journal of Sensor Science and Technology
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• v.14 no.6
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• pp.402-408
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• 2005

This paper describes the optimal design of a multi-layered surface plasmon resonance sensors to meet various specifications and improve some physical parameters. Dip 3 dB bandwidth and depth were chosen as design parameters and the objective function was the norm of the difference between design parameters and target values. The design variables are thicknesses of each layer and to obtain the design parameters, the optical admittance method was employed. The (1+1) evolution strategy was employed as an optimization tool. By applying the proposed optimization procedure to a 3-layered sensor, the optimized design variables considerably improved the 3 dB bandwidth by 4.8 nm and the dip depth by 1.1 dB.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.616-617
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• 2013

This paper introduces a new method that controls a humanoid robot detecting a human motion using a Kinect sensor. Processing the output of a depth seneor of the Kinect sensor, we build a human stick model which represents each joint of human body. We detect a specific motion by calculating the distance and angle between joints. We send the control message to the robot using Bluetooth wireless communication.