• 한국항해항만학회지
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• 제38권6호
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• pp.645-653
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• 2014

A Bridge Navigational Watch Alarm System (hereafter 'BNWAS') is to monitor and detect if an officer of watch(hereafter 'OOW') keeps a sharp lookout on the bridge. The careless lookout of an OOW could lead to marine accidents. For this reason on June 5th, 2009, IMO decided that a ship is equipped with a BNWAS. However, an existing BNWAS gives the OOW a lot of inconvenience and stress in its operation. It requires that the OOW should press reset buttons to confirm their alert watch on the bridge at every three to twelve minute. Many OOWs have complained that at some circumstances they cannot focus on their bridge activities including watch-keeping due to a lots of resetting inputs of BNWAS. Accordingly, IMO has allowed the use of a motion sensor as a resetting device. The motion sensor detects the movements of human body on the bridge and subsequently sends reset signals directly to BNWAS automatically. As a result, OOWs can work uninterrupted. However, some of classification societies and flag authorities have a slightly different stance on the use of motion sensor as a resetting method for BNWAS. The reason is that the motion sensor may trigger false reset signals caused by the motion of objects on the bridge, especially a slight movement such as toss and turn of human body which can extend the period of careless watch. As a basic study to minimize the false reset signals, this paper proposes a simple configuration of BNWAS, which consists of only three motion sensors associated with 'AND' and 'OR' logic gates. Additionally, several considerations are also proposed for the implementation of motion sensors. This study found that the proposed configuration which consists of three motion sensors is better than an existing one by reducing false reset signals caused by a slight movement of human body in one's sleep. The proposed configuration in this paper filters false reset signals and is simple to be implemented on existing vessels. In addition, it can be easily installed just by a basic electrical knowledge.

• 방송공학회논문지
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• 제20권4호
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• pp.557-567
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• 2015

정지영상에서 공간 관심맵을 생성하는 다양한 방법들이 소개되어 왔고, 최근에는 동영상의 운동정보를 활용하는 운동 관심맵 예측 기법이 활발히 연구되고 있다. 운동 관심맵은 운동정보 및 영역분할을 활용하고 있지만, 일반적인 영상에서는 만족스러운 데이터를 얻는 것은 어려움이 존재한다. 또한 우수한 관심맵을 얻기 위해서는 객체 운동, 카메라 운동 등의 운동유형 정보가 필요하기 때문에 다양한 자연영상을 대상으로 적용하면 성능 저하가 발생한다. 본 논문에서는 상기 언급한 문제점들을 극복할 수 있는 운동기반 관심맵 생성 방법을 제안한다. 공간 관심맵에 운동 정보를 결합하고, 운동 복잡도를 활용한다. 또한 근접 모델을 이용하여 주변 픽셀들의 관심도를 유사하게 함으로써, 동일 객체 또는 배경 영역이 유사한 값을 가지도록 한다. 실험에서는 다양한 동영상 데이터에 제안 방법을 적용하여 성능 검증을 수행하였다. 공간 관심도의 개선 여부를 증명하기 위해서 공간 관심맵 방법과의 객관적 성능 평가를 통해서 제안 방법이 공간 관심맵보다 운동 픽셀의 경우에 평균적으로 관심도 값이 +38 정도 향상되는 것을 보여준다. 또한 참조 데이터가 있는 4개의 동영상을 대상으로 얻은 ROC는 만족스러운 결과를 보여준다.

• 제어로봇시스템학회논문지
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• 제21권6호
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• pp.547-552
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• 2015

In this paper, an ARS-EKF based motion counting algorithm for repetitive exercises such as calisthenics is proposed using a smartwatch. Raw sensor signals from accelerometers and gyroscopes are widely used for conventional smartwatch counting algorithms based on pattern recognition. However, generated features from raw data are not intuitive to reflect the movement of motions. The proposed motion counter algorithm is composed of navigation based feature generation and counting with error correction. The candidate features for each activity are velocity and attitude calculated through an ARS-EKF algorithm. In order to select those features which reveal the characteristics of each motion, an exercise frame from the initial sensor frame is introduced. Counting processes are basically based on the zero crossing method, and misdetected counts are eliminated via simple classification algorithms considering the frequency of the counted motions. Experimental results show that the proposed algorithm efficiently and accurately counts the number of exercises.

• IEIE Transactions on Smart Processing and Computing
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• 제5권5호
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• pp.327-330
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• 2016

Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.

• 한국통신학회논문지
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• 제36권2C호
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• pp.78-85
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• 2011

본 논문에서는 카메라 자체에서 움직임을 검출하고 분류된 객체를 추척할 수 있는 지능형 PTZ 카메라 시스템을 제안하였다. 추적하고자 하는 객체가 검출되면 분류하고, 객체의 움직임에 따라 PTZ 카메라가 실시간으로 추적한다. 검출을 위해 GMM을 사용하였고 검출성능을 높이기 위해 그림자 제거 기법을 적용하였다. 검출된 객체의 분류를 위해 Legendre 모멘트를 적용하였다. 본 논문에서는 카메라의 초점 조절을 사용하지않고 영상의 중심과 객체와의 방향, 거리, 속도 정보만을 이용하여 PTZ 카메라의 움직임을 제어하는 방법을 제안하였다. TI DM6446 Davinci를 이용하여 실시간으로 객체의 검출, 분류와 추적이 가능한 카메라 시스템을 구성하였다. 실험 결과 사람과 차량을 구분하고, 움직임의 속도가 빠른 차량에 대해서도 본 추적시스템은 안정적으로 동작함을 확인하였다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2011년도 추계학술대회
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• pp.143-146
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• 2011

This paper presents human perception-based video coding method using an online learning framework. In this work, we analyze the relationship between human attention regions and video quality, and also consider human memory. We classify the motion patterns based on the analysis. Then, we devise a motion pattern classification method using Hedge algorithm. Along with the motion patterns, we smooth out the specific regions or sharpen details of the regions using the regional priorities. The preprocessed sequences are applied to the video codec. The performance is excellent on the overall quality as well as the regional quality.

• 융합신호처리학회논문지
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• 제5권4호
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• pp.287-293
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• 2004

본 논문은 밝기 변화가 심한 비디오 시퀀스에 대해 효율적인 움직임 보상 알고리즘을 제안한다. 제안한 알고리즘에서는 화면간의 밝기 변화 변수들을 추정하고 지역적인 움직임 보상을 수행한다. 밝기 변화가 심한 화면을 검출하기 위해 연속되는 두 프레임간의 히스토그램의 크로스 엔트로피를 계산하여 밝기 변화가 심한 화면을 그렇지 않은 화면과 나누어 밝기 변화가 심하지 않은 경우에 발생할 수 있는 불필요한 계산량을 줄였다. 밝기 변화가 심한 비디오 시퀀스에 대한 실험결과 제안한 알고리즘은 기존의 알고리즘에 비해 적은 계산량으로 높은 PSNR (peak signal to noise ratio) 성능을 나타내었다.

• 대한전기학회논문지
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• 제33권10호
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• pp.381-386
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• 1984

This paper deals with the microcomputer realization of EMG pattern recognition system which provides identification of motion commands from the EMG signals for the on-line control of a prosthetic arm. A probabilistic model of pattern is formulated in the feature space of integral absolute value(IAV) to describe the relation between a motion command and the location of corresponding pattern. This model enables the derivation of sample density function of a command in the feature space of IAV. Classification is caried out through the multiclass sequential decision process, where the decision rule and the stopping rule of the process are designed by using the simple mathematical formulas defined as the likelihood probability and the decision measure, respectively. Some floating point algorithms such as addition, multiplication, division, square root and exponential function are developed for calculating the probability density functions and the decision measure. Only six primitive motions and one no motion are incorporated in this paper.

• 스마트미디어저널
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• 제8권3호
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• pp.47-52
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• 2019

In this paper, we designed HW / SW interfaces for processing the signals of capacitive sensors like Electric Potential Sensor (EPS) to detect the surrounding electric field disturbance as feature signals in motion recognition systems. We implemented a smart light control system with those interfaces. In the system, the on/off switch and brightness adjustment are controlled by hand gestures using the designed and fabricated interface circuits. PWM (Pulse Width Modulation) signals of the controller with a driver IC are used to drive the LED and to control the brightness and on/off operation. Using the hand-gesture signals obtained through EPS sensors and the interface HW/SW, we can not only construct a gesture instructing system but also accomplish the faster recognition speed by developing dedicated interface hardware including control circuitry. Finally, using the proposed hand-gesture recognition and signal processing methods, the light control module was also designed and implemented. The experimental result shows that the smart light control system can control the LED module properly by accurate motion detection and gesture classification.

• ETRI Journal
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• 제46권2호
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• pp.250-262
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• 2024

Air-writing recognition is relevant in areas such as natural human-computer interaction, augmented reality, and virtual reality. A trajectory is the most natural way to represent air writing. We analyze the recognition accuracy of words written in air considering five features, namely, writing direction, curvature, trajectory, orthocenter, and ellipsoid, as well as different parameters of a hidden Markov model classifier. Experiments were performed on two representative datasets, whose sample trajectories were collected using a Leap Motion Controller from a fingertip performing air writing. Dataset D₁ contains 840 English words from 21 classes, and dataset D₂ contains 1600 English words from 40 classes. A genetic algorithm was combined with a hidden Markov model classifier to obtain the best subset of features. Combination ftrajectory, orthocenter, writing direction, curvatureg provided the best feature set, achieving recognition accuracies on datasets D₁ and D₂ of 98.81% and 83.58%, respectively.