• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.301-314
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• 2008

The existing event recognition is accomplished with the limited systematic foundation, and thus much longer learning time is needed for emergency scenario interpretation due to large scale of probability data. In this paper, we propose a method for nile-based event recognition of an independent object(human) which extract a feature vectors from the object and analyze the behavior pattern of each object and interpretation of emergency scenarios using a probability and object's events. The event rule of an independent object is composed of the Primary-event, Move-event, Interaction-event, and 'FALL DOWN' event and is defined through feature vectors of the object and the segmented motion orientated vector (SMOV) in which the dynamic Bayesian network is applied. The emergency scenario is analyzed using current state of an event and its post probability. In this paper, we define diversified events compared to that of pre-existing method and thus make it easy to expand by increasing independence of each events. Accordingly, semantics information, which is impossible to be gained through an.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1670-1683
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• 2017

Mitotic event recognition is a crucial and challenging task in biomedical applications. In this paper, we introduce the slow feature analysis and propose a fully-automated mitotic event recognition method for cell populations imaged with time-lapse phase contrast microscopy. The method includes three steps. First, a candidate sequence extraction method is utilized to exclude most of the sequences not containing mitosis. Next, slow feature is learned from the candidate sequences using slow feature analysis. Finally, a hidden conditional random field (HCRF) model is applied for the classification of the sequences. We use a supervised SFA learning strategy to learn the slow feature function because the strategy brings image content and discriminative information together to get a better encoding. Besides, the HCRF model is more suitable to describe the temporal structure of image sequences than nonsequential SVM approaches. In our experiment, the proposed recognition method achieved 0.93 area under curve (AUC) and 91% accuracy on a very challenging phase contrast microscopy dataset named C2C12.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.199-204
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• 2008

Visual surveillance is an active topic recently in Computer Vision. Event detection and recognition is one important and useful application of visual surveillance system. In this paper, we propose a new method to recognize the entering and exiting events based on the human's movement feature and the door's state. Without sensors, the proposed approach is based on novel and simple vision method as a combination of edge detection, motion history image and geometrical characteristic of the human shape. The proposed method includes several applications such as access control in visual surveillance and computer vision fields.

• Journal of the Korean Society of Food Culture
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• v.29 no.4
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• pp.314-325
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• 2014

To contribute to the globalization of Korean food, a Korean food culture publicity event was conducted at Hayabusa Station, Tottori Province, Japan. This study investigated and analyzed recognition and preferences towards Korean food in participants at the event. The method of information acquisition was also analyzed. Most participants had prior experience eating Korean food. As for information, participants responded that they were affected by public media such as dramas, and the most effective way of getting information was participating in lectures. This study also investigated intake of 20 kinds of Korean food and found highest preferences for bibimbap, kimchi, naengmyeon, and galbigui, in that order. The main motive for participating in the Korean food culture publicity event was a desire to experience a new culture. Further, satisfaction, intention to participate, and intention to recommend Korean food were high. These attitudes had significant effects on the intention to visit Korea. In the future, Korean food culture publicity events held in foreign lands can contribute to Korean tourism.

• Journal of the Korean Society of Food Culture
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• v.29 no.6
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• pp.528-538
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• 2014

The purpose of this study was to investigate the relationships among recognition, preference, and purchasing characteristics for Changnyeong onions and garlic as well as festival satisfaction among participants at agricultural product festivals in the Changnyeong region. Results showed that festival satisfaction of 'place of festival' was highest while 'convenience facility & event contents' earned the lowest scores. Most subjects (90.5%) had purchased Changnyeong agricultural and processed products. A major purchasing type was fresh agricultural products (66.7%). The pathways to recognize Changnyeong agricultural products were mostly 'promotion by related institutions' (22.0%), 'family relatives' (20.8%), 'mass media' (16.6%), and 'festivals and events' (16.1%). The most considered factors for purchasing regional products were 'geographical origin' and 'ingredients'. Changnyeong onion showed higher scores for recognition and preference and rate of purchase experience and intention than for garlic. The correlation coefficients of recognition and preference for onion and galic were 0.603 (p<0.001) and 0.598 (p<0.001), respectively. The explanation power ($R^2$) of related variables for purchase of Changnyeong onions was 0.258. The regression coefficients (${\beta}$) for 'recognition', 'preference' and 'convenient facility & event contents' were positive, whereas the regression coefficient for 'price' was negative. Recognition, preference, and convenient facility & event contents with garlic purchase showed a positive relationship ($R^2$=0.253). The most effective promotion method to increase sales of Changnyeong agricultural products was 'local festivals and events' (27.8%).

• The Korean Journal of Legal Medicine
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• v.39 no.4
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• pp.115-119
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• 2015

We investigated event-related potentials (ERPs) to estimate the accuracy of eyewitness memories. Participants watched videos of vehicles being driven dangerously, from an anti-impaired driving initiative. The four-letter license plates of the vehicles were the target stimuli. Random numbers were presented while participants attempted to identify the license plate letters, and electroencephalograms were recorded. There was a significant difference in activity 300-500 milliseconds after stimulus onset, between target stimuli and random numbers. This finding contributes to establishing an eyewitness recognition model where different ERP components may reflect more explicit memory that is dissociable from recollection.

• Journal of Drive and Control
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• v.17 no.3
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• pp.9-14
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• 2020

A special purpose machine with two manipulators and quadruped crawler system is being developed to work at disaster sites where it is intended to quickly respond in the initial stages after the event. In this study, a terrain recognition module is developed so that the above special purpose machine can quickly obtain ground information to help choose its path while recognizing objects in its way, this is intended to enhance the remote driver's limited situational awareness. Terrain recognition modules were developed for two tasks (real-time path guidance, precision terrain measurements). The real-time path guidance analyzes terrain and obstacles while moving, while the precision terrain measurement feature provides more accurate terrain information by precisely measuring the ground in front of the vehicle while stationary. In this study, an air-cooled sensor protection module was developed so that the terrain recognition module can continue its vital tasks in the event of exposure to foreign substances, including scattered dust, mist and rainfall, as well as high temperatures.

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.16-21
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• 2015

In this paper, we presented Under Vehicle Inspection System by comparing two image signals. Two signals are generated by license plate number and under-vehicle pattern recognition. The test shows reliable precision within real-time of 2.8sec, which can be applicable commercially. In the future, more research will be conducted to enhance the precision by automatic image balance in many challenging situations.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.263.2-263.2
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• 2013

We report a systematic investigation of a set of macrophotoinitiators for use in polymerization-based signal amplification. To test the dependence of photopolymerization responses on the number of photoinitiators localized per molecular recognition event, we gradually increased the number of photoinitiator molecules coupled to a scaffold macromolecule. Macrophotoinitiators constructed with an average of 7 to 168 photoinitiators per polymer with the goals of quantifying the relationship between the number of initiators per binding event and the degree of amplified colorimetric readout. To evaluate the capacity of the macrophotoinitiators to detect molecular recognition, neutravidin was coupled to these molecules to recognize biotin-labeled DNA immobilized on biochip test surfaces. Fluorescein macroinitiators are found to be useful in detecting molecular recognition above a threshold of initiators per polymer. Above this threshold, increasing the number of initiators per macroinitiator resulted in increased signal strength.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.273-281
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• 2022

In this paper, we propose a robot sound recognition system that detects various sound events. The proposed system is designed to detect various sound events in real-time by using a microphone on a robot. To get real-time performance, we use a VGG11 model which includes several convolutional neural networks with real-time normalization scheme. The VGG11 model is trained on augmented DB through 24 kinds of various environments (12 reverberation times and 2 signal to noise ratios). Additionally, based on random forest algorithm, a decision logic is also designed to generate event signals for robot applications. This logic can be used for specific classes of acoustic events with better performance than just using outputs of network model. With some experimental results, the performance of proposed sound recognition system is shown on real-time device for robots.