Minsoo Hahn

Three-dimensional electro-floating display system using an integral imaging method

A new-type of three-dimensional (3D) display system based on two different techniques, image floating and integral imaging, is proposed. The image floating is an antiquated 3D display technique, in which a large convex lens or a concave mirror is used to display the image of a real object to observer. The electro-floating system, which does not use a real object, requires a volumetric display part in order to present 3D moving pictures. Integral imaging is an autostereoscopic technique consisting of a lens array and a two-dimensional display device. The integral imaging method can be adapted for use in an electro-floating display system because the integrated image has volumetric characteristics within the viewing angle. The proposed system combines the merits of the two techniques such as an impressive feel of depth and the facility to assemble. In this paper, the viewing characteristics of the two techniques are defined and analyzed for the optimal design of the proposed system. The basic experiments for assembling the proposed system were performed and the results are presented. The proposed system can be successfully applied to many 3D applications such as 3D television.

Determining location of appliances from multi-hop tree structures of power strip type smart meters

Recently, energy management has become one of the emerging services in the area of residential network service. A smart meter is the most essential component of advanced metering infrastructure (AMI) that connects the home energy management system of individual residences and a smart grid that optimizes the production, distribution, and consumption of electric power. Power strip type smart meters can be used to not only monitor but also control the electric power consumption at individual power outlet ports in the power outlet directly. They can be used to control and effectively reduce standby power consumption by the application of the direct power supply control. A smart multi-power tap (SMPT) is an advanced multi-outlet power strip type smart meter that provides important contextual information such as the identity and location of electric home appliances on the basis of the temporal power consumption data and the control of power supply to the appliances. However, the SMPT cannot be used to determine the location of appliances when the connections among SMPTs form a tree structure. In this study, we develop a mathematical model of cascade connections among SMPTs and propose a solution for obtaining the location information of the tree structure. The proposed method helps realize real applications of the SMPT for providing activity-based context-aware home network services and energy management services.

HMM-based Korean speech synthesis system for hand-held devices

Speech interface may be the first choice as a user interface for robots or hand-held devices such as personal digital assistants (PDAs) and portable multimedia players (PMPs). However, those devices have the limitation of the memory space and the computation power. The hidden Markov model (HMM)-based speech synthesis is presently considered to be suitable for the embedded systems. In this paper, our HMM-based Korean speech synthesis system is described. Statistical HMM models for Korean speech units are trained with the hand-labeled speech database including the contextual information about phoneme, word phrase, and multilevel break strength. Mel-cepstrum and line spectrum pair (LSP) are compared for the spectrum modeling, and two-band excitation based on the harmonic plus noise speech model is utilized for the mixed excitation source. The developed small-size Korean synthesis system produced considerably high quality speech with a fairly good prosody

Enhanced Image Mapping Algorithm for Computer-Generated Integral Imaging System

An enhanced image mapping algorithm is proposed for a real-time computer-generated (CG) integral imaging system. The proposed algorithm, viewpoint vector rendering, can be easily adapted to generate a set of elemental images from complex three-dimensional (3D) objects and is less affected by system factors and object image quality than previous methods. In addition, it can support all the display modes of the integral imaging system. The feasibility and efficiency of the proposed approach are verified and analyzed through rendering experiments. Using this technique, it is possible to realize an interactive CG integral imaging system which can be applied to virtual reality.

Measurement of initial motion of a flying golf ball with multi-exposure images for screen-golf

Recently, realistic sports games have been one of the growth industries of the indoor entertainment field. In particular, screen-golf, which is played indoors with real golf clubs and balls, has shown an outstanding growth rate in South Korea. It consists of a sensor, a computer graphics engine, an interior, and other elements. The sensor is the most essential component among them. It measures the initial conditions of a flying golf ball, the velocity, the horizontal angle, and the vertical angle. Until 2008, most commercialized products were infrared LED type sensors, but these are associated with relatively low accuracy and a narrow measurement range compared to those that utilize a camera. In spite of the better performance, camera-based screen-golf sensors are not broadly employed in the screen-golf market because they remain expensive compared with other screen-golf sensors. In this study, a new type of camera-based sensor system that captures multi-exposure images and ball tracking algorithms are suggested. These measure the initial condition of a flying golf ball from captured images. The suggested system was verified in an environment equal to that of a real screen-golf store.

Drowsy Driving Detection Based on the Driver's Head Movement using Infrared Sensors

In the driving circumstance, the driver¿s condition is directly connected with the car accident. Therefore, there are many researches to decrease the car accidents by keeping the driver¿s state in a good condition. While many of these researches are focused on the driver¿s face, our approach is focused on the driver¿s head movement. By collecting the driver¿s head position and extracting the feature points, the proposed system calculates the driver¿s physical state: Normal driving or Drowsy driving. The experimental results showed 78% of success rate to find the drowsy driving in the real driving situations.

A Knowledge-Based Approach to Arterial Stiffness Estimation Using the Digital Volume Pulse

We have developed a knowledge based approach for arterial stiffness estimation. The proposed new approach reliably estimates arterial stiffness based on the analysis of age and heart rate normalized reflected wave arrival time. The proposed new approach reduces cost, space, technical expertise, specialized equipment, complexity, and increases the usability compared to recently researched noninvasive arterial stiffness estimators. The proposed method consists of two main stages: pulse feature extraction and linear regression analysis. The new approach extracts the pulse features and establishes a linear prediction equation. On evaluating proposed methodology with pulse wave velocity (PWV) based arterial stiffness estimators, the proposed methodology offered the error rate of 8.36% for men and 9.52% for women, respectively. With such low error rates and increased benefits, the proposed approach could be usefully applied as low cost and effective solution for ubiquitous and home healthcare environments.

Performance improvement of pulse oximetry-based respiration detection by selective mode bandpass filtering

In this paper, an improved method to detect respirations by pulse oximetry during exercise is proposed. As a method for robust respiration detection, fixed bandpass filtering to block the heart beat signals is commonly utilized. But the fixed bandpass filtering cannot guarantee reasonable performances when the HR(Heart Rate) is varied highly. Therefore, the respiration detection performance is degraded. In the proposed algorithm, the HR information is used to estimate the RR(Respiration Rate). Using the RR, the corresponding bandpass filter(BPF) is selected to detect respiration points. The selection of the passband makes the proposed algorithm possible to guarantee the performance during exercise. Our test results show that the overall estimation error of the proposed algorithm was 20.32% during exercise.

Implementation and Evaluation of an HMM-Based Korean Speech Synthesis System

Development of a hidden Markov model (HMM)-based Korean speech synthesis system and its evaluation is described. Statistical HMM models for Korean speech units are trained with the hand-labeled speech database including the contextual information about phoneme, morpheme, word phrase, utterance, and break strength. The developed system produced speech with a fairly good prosody. The synthesized speech is evaluated and compared with that of our corpus-based unit concatenating Korean text-to-speech system. The two systems were trained with the same manually labeled speech database.

A Robust Method for Pulse Peak Determination in a Digital Volume Pulse Waveform With a Wandering Baseline

This paper presents a robust method for pulse peak determination in a digital volume pulse (DVP) waveform with a wandering baseline. A proposed new method uses a modified morphological filter (MMF) to eliminate a wandering baseline signal of the DVP signal with minimum distortion and a slope sum function (SSF) with an adaptive thresholding scheme to detect pulse peaks from the baseline-removed DVP signal. Further in order to cope with over-detected and missed pulse peaks, knowledge based rules are applied as a postprocessor. The algorithm automatically adjusts detection parameters periodically to adapt to varying beat morphologies and fluctuations. Compared with conventional methods (highpass filtering, linear interpolation, cubic spline interpolation, and wavelet adaptive filtering), our method performs better in terms of the signal-to-error ratio, the computational burden (0.125 seconds for one minute of DVP signal analysis with the Intel Core 2 Quad processor @ 2.40 GHz PC), the true detection rate (97.32% with an acceptance level of 4 ms ) as well as the normalized error rate (0.18%). In addition, the proposed method can detect true positions of pulse peaks more accurately and becomes very useful for pulse transit time (PTT) and pulse rate variability (PRV) analyses.