• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.556-565
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• 2014

This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.197-200
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• 2014

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image. The proposed method produces good results of facial expression and discriminates risk situation well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.523-528
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image to recognize facial expression. The DB has 6 kinds of facial expressions of human being that are basic facial expressions such as smile, sadness, surprise, anger, disgust, and fear expression. The proposed method produces good results of facial expression and discriminates risk situation well.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.51-55
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing dangerous situation. The proposed method firstly extracts the facial region using Harr-like technique from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, detects facial expression, and recognizes dangerous situation. The proposed method is evaluated for MUCT database image and web cam input. The proposed method produces good results of facial expression and discriminates dangerous situation well and the average recognition rate is 91.05%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.173-174
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• 2019

In this paper, we study the transmission of real-time information to the recognition of risk situation. Through analyzing the scenario of risk situation to the mobile object, immediate information providing should be transmitted to the management system if a risk occurs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3412-3420
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• 2015

Smartphone has become an essential element in our daily life and built-in sensors of the smartphone can be utilized in order to recognize of user's situation. However, it is lack of research for safety and accident prevention by dynamic situation recognition. In this paper, we propose a technique that can be recognized risk situation dynamically using accelerometer, microphone and GPS sensor of mobile device. We propose an architecture and process for sensing techniques of Dynamic Recognition Technique, and develop the mobile application for verifying the suitability of the architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.171-172
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• 2019

In this paper, we consider the dynamic method for the searching development of Web map to the monitoring object in the risk environments. It is to recognize the real-time detection to the risk situation based on the location monitoring mechanism of management to the object movement.

• Journal of Navigation and Port Research
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• v.36 no.4
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• pp.279-284
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• 2012

This study aims to identify the degree of safety when mariners take their actions in several different situations. We have carried out many experiments to observe mariners' behavior and then measured the safety level based on their actions to avoid dangerous situations of ships collision. One of the most important actions that mariners have to take, either as their daily routine or when they are in a collision situation and then want to avoid that situation is the lookout. In this paper, behaviors on the lookout have been defined as a standard sequence of three steps which are "time of first detection", "time of recognition as risky vessel" and "time of starting avoiding action", and the suitability and applicability of the definition have been shown. And also we propose the risk assessment on ships collision and the recommendation for reducing ships collision at sea. Some analyzing results and the application of the results are reported. By combining these knowledge and some systematic studies, we propose the risk assessment on ships collision and the recommendation for reducing ships collision at sea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1693-1700
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• 2012

Recently, the warning system to aid drivers for safe driving is being developed. The system estimates the distance between the driver's car and the car before it and informs him of safety distance. In this paper, we designed and implemented the collision warning system which detects the car in front on the actual road situation and measures the distance between the cars in order to detect the risk situation for collision and inform the driver of the risk of collision. First of all, using the forward-looking camera, it extracts the interest area corresponding to the road and the cars from the image photographed from the road. From the interest area, it extracts the object of the car in front through the analysis on the critical value of the shadow of the car in front and then alerts the driver about the risk of collision by calculating the distance from the car in front. Based on the results of detecting driving cars and measuring the distance between cars, the collision warning system was designed and realized. According to the result of applying it in the actual road situation and testing it, it showed very high accuracy; thus, it has been verified that it can cope with safe driving.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.44-50
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• 2017

To understand whether Falling, which is one of the causes of injuries, occurs, various behavior recognition research is proceeding. However, in most research recognize only the fact that Falling has occurred and provide the service. As well as the occurrence of the Falling, the risk varies greatly based on the type of Falling and the situation before and after the Falling. Therefore, when Falling occurs, it is necessary to infer the user's current situation and provide appropriate services. In this paper, we propose to base on Fog Computing and Cloud Computing to design Context-aware System using analysis of behavior data and process sensor data in real-time. This system solved the problem of increase latency and server overload due to large capacity sensor data.