• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3322-3337
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• 2018

Sleep mode detection is a significant power management and green computing feature. However, it is difficult for televisions and smart TVs to detect deactivation events because we can use these devices without the assistance of an input device. In this paper, we propose a robust method for smart TVs to detect deactivation events based on a visual combination of face and motion detection. The results of experiments conducted indicate that the proposed method significantly reduces incorrect face detection and human absence by means of motion detection. The results also show that the proposed method is robust and effective for smart TVs to reduce power consumption.

• ETRI Journal
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• v.33 no.2
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• pp.259-266
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• 2011

We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: I) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a k-nearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1279-1282
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• 2003

Estimation of human motion states is important enabling technologies for realizing a pervasive computing environment. In this paper, an improved method fur estimating human motion state from accelerometer data is introduced. Our method fur estimating human motion state utilizes various statistics of accelerometer data, such as mean, standard variation, skewness, kurtosis, eccentricity, as features for classification, and therefore is expected to be more robust than other existing methods that rely on only a few simple statistics. A series of experiments fur testing the effectiveness of the proposed method has been performed, and its result is presented.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2120-2123
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• 2003

This paper presents the moving object detection and tracking algorithm using edge information base on human perceptual system The human visual system recognizes shapes and objects easily and rapidly. It's believed that perceptual organization plays on important role in human perception. It presents edge model(GCS) base on extracted feature by perceptual organization principal and extract edge information by definition of the edge model. Through such human perception system I have introduced the technique in which the computers would recognize the moving object from the edge information just like humans would recognize the moving object precisely.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.6
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• pp.66-71
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• 2007

Development of a locomotive mechanism for the capsule type endoscopes will largely enhance their ability to diagnose disease of digestive organs. As a part of it, there should be provided a detection device of their position in human organs for the purpose of observation and motion control. In this paper, a permanent magnet outside human body was employed to project magnetic field on a capsule type endoscope, while its position dependent flux density was measured by three hall-effect sensors which were orthogonally installed inside the capsule. In order to detect the 2-D position data of the capsule with three hall-effect sensors including the roll, pitch and yaw angle, the permanent magnet was extra translated during the measurement. In this way, the 2-D coordinates and three rotation angles of a capsule endoscope on the same motion plane with the permanent magnet could be detected. The working principle and performance test results of the capsule position detection device were introduced in this paper showing that they could be also applied to 6-DOF position detection.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.501-507
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• 2012

Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human hand motion recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users' skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved Camshift tracking algorithm is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.202-205
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• 2000

In this paper we propose an algorithm that detects, tracks a moving object, and classify whether it is human from the video clip captured under the fixed video camera. It detects the outline of the moving object by finding out the local maximum points of the modulus image, which is the magnitude of the motion vectors. It also estimates the size and the center of the moving object. When the object is detected, the algorithm discriminates whether it is human by segmenting the face. It is segmented by searching the elliptic shape using Hough transform and grouping the skin color region within the elliptic shape.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.625-626
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• 2013

This paper introduces a new method that detects human motions using a Kinect sensor. Also this paper describes a method to mimic the detected human motions. We first build a human stick model by processing the output of Kinect sensor. We detect a specific motion by using the position of each joint of the human stick model and by using the angles between joints.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.57-64
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• 2015

In this paper, we propose a design of microwave motion detector using X-band doppler radar sensor to minimize the power consumption. To minimize the power consumption and implement battery operated system, pulse input with 2 KHz, 4% duty cycle is exerted on the doppler radar sensor. In order to simplify the process of working with ATmega2560 microcontroller unit, Arduino compatible board is designed and implemented. Arduino is open source hardware and many library software is published as open source tools. Smartphone app is also proposed and designed as a real-time user interface of the motion detector. The SQLite database on the Android mobile operating system is used for recording raw data of motion detection for post-processing job, such as fast Fourier transform (FFT). Bluetooth interface module is implemented on the motion detection board as a wireless communication interface to the smartphone. The speed of human movement is identified by post-processing FFT.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.124-131
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• 2017

This paper present a novel approach to control the lower body power assistive exoskeleton system of a HEXAR-CR35 aimed at improving a muscular strength. More specifically the control of based on the human intention is crucial of importance to ensure intuitive and dexterous motion with the human. In this contribution, we proposed the detection algorithm of the human intention using the MCRS which are developed to measure the contraction of the muscle with variation of the circumference. The proposed algorithm provides a joint motion of exoskeleton corresponding the relate muscles. The main advantages of the algorithm are its simplicity, computational efficiency to control one joint of the HEXAR-CR35 which are consisted knee-active type exoskeleton (the other joints are consisted with the passive or quasi-passive joints that can be arranged by analyzing of the human joint functions). As a consequence, the motion of exoskeleton is generated according to the gait phase: swing and stance phase which are determined by the foot insole sensors. The experimental evaluation of the proposed algorithm is achieved in walking with the exoskeleton while carrying the external mass in the back side.