• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.279-287
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• 2006

This paper proposes a method to detect fall action by using stereo images to recognize emergency situation. It uses 3D information to extract the visual information for learning and testing. It uses HMM(Hidden Markov Model) as a recognition algorithm. The proposed system extracts background images from two camera images. It extracts a moving object from input video sequence by using the difference between input image and background image. After that, it finds the bounding rectangle of the moving object and extracts 3D information by using calibration data of the two cameras. We experimented to the recognition rate of fall action with the variation of rectangle width and height and that of 3D location of the rectangle center point. Experimental results show that the variation of 3D location of the center point achieves the higher recognition rate than the variation of width and height.

• Phonetics and Speech Sciences
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• v.4 no.1
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• pp.77-87
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• 2012

Interest in music recognition has been growing dramatically after NHN and Daum released their mobile applications for music recognition in 2010. Methods in music recognition based on audio analysis fall into two categories: music recognition using audio fingerprint and Query-by-Singing/Humming (QBSH). While music recognition using audio fingerprint receives music as its input, QBSH involves taking a user-hummed melody. In this paper, research trends are described for music recognition using audio fingerprint, focusing on two methods: one based on fingerprint generation using energy difference between consecutive bands and the other based on hash key generation between peak points. Details presented in the representative papers of each method are introduced.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.54-64
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• 2013

In this study, we developed a falling recognition system to transmit SMS data through CDMA communication using a three axises acceleration sensor and a two axises gyro sensor. 5 healthy men were selected into a control group, and the fall recognition system using the three axises acceleration sensor and the two axises gyro sensor was devised to conduct an experiment. The system was attached to the upper of their sternum. According to the experiment protocol, the experiment was carried out 3 times repeatedly divided into 3 specific protocols: falling during gait, falling in stopped state, and falling in everyday life. Data obtained in the falling recognition system and LabVIEW 8.5 were used to decide if falling corresponds to that regulated in an analysis program applying an algorithm proposed in this study. In addition, results from falling recognition were transmitted to designated cellular phone in a SMS (Shot Message Service) form. These research results show that an erroneous detection rate of falling reached 19% in applying an acceleration signal only; 6% in applying an angular velocity; and 2% in applying a proposed algorithm. Such finding suggests that an erroneous detection rate of falling is improved when the proposed algorithm is applied incorporated with acceleration and angular velocity. In this study therefore, we proposed that a falling recognition system implemented in this study can make a contribution to the recognition of falling of the aged or the disabled.

• Journal of IKEEE
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• v.18 no.1
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• pp.134-139
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• 2014

According to survey, more than 57.2% of the fall which is the most frequent safety accident of the elders takes place at home. This research aims to verify the fall by measuring and analyzing the floor vibration. And the vibration sensor module was designed with piezo film sensor and operation amplifier. The vibration signals are converted to digital signals through the data acquisition device and vibration sensor module. And then modified the signals into frequency domain to obtain characteristic vibration data. The characteristic signals are verified by K-Nearest Neighbor verification, and experimental results shows the recognition rate 93.6%. Also the fall detection sensor module is useful for extract the meaningful data for fall detection. 10 persons are participated for this experiment.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.471-477
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• 2018

As an important key technology using on electronic devices, face recognition has become one of the hottest technology recently. The traditional BP Neural network has a strong ability of self-learning, adaptive and powerful non-linear mapping but it also has disadvantages such as slow convergence speed, easy to be traversed in the training process and easy to fall into local minimum points. So we come up with an algorithm based on BP neural network but also combined with the PCA algorithm and other methods such as the elastic gradient descent method which can improve the original network to try to improve the whole recognition efficiency and has the advantages of both PCA algorithm and BP neural network.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.88-95
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• 2003

The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

• 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.

• Proceedings of the KAIS Fall Conference
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• 2010.11a
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• pp.200-202
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• 2010

본 논문에서는 유아환경 인식변화를 위한 환경교육용 2D 웹 콘텐츠를 구현하여 유아가 손쉽게 활용하고 유아환경 인식 변화를 향상시킬 수 있는 웹 콘텐츠를 구현하는 것을 최종목표로 한다.

• MALSORI
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• no.41
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• pp.73-81
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• 2001

This paper reports the results of an experimental phonetic study of intonation contrasts perception by speakers of British English, Japanese and Russian. Six series of re-synthesized two-syllable rise-fall contours with manipulated parameters of the rise in the first and the fall in the second syllable were employed in the experiment. Modifications of pitch height were executed in 2 st steps, and of duration in 30ms steps. The subjects, who were native speakers of British English, Japanese and Russian, identified the sentence type of presented re-synthesized stimuli. The results of the experiments demonstrate overall similarity of the perception strategies across the three groups of subjects, especially regarding the thresholds of declarative' sentence type judgement. Non-declarative judgements are more language-specific. The results can be employed for the teaching of English, Japanese and Russian as foreign languages as well as for speech synthesis and recognition.

• Proceedings of the KSPS conference
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• 2000.07a
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• pp.139-148
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• 2000

This paper reports the results of an experimental phonetic study of intonation contrasts perception by speakers of British English, Japanese and Russian. Six series of re-synthesized two-syllable rise-fall contours with manipulated parameters of the rise in the first and the fall in the second syllable were employed in the experiment. Modifications of pitch height were executed in 2 st steps, and of duration - in 30ms steps. The subjects, who were native speakers of British English, Japanese and Russian, identified the sentence type of presented re-synthesized stimuli. The results of the experiments demonstrate overall similarity of the perception strategies across the three groups of subjects, especially regarding the thresholds of 'declarative' sentence type judgement. Non-declarative judgements are more language-specific. The results can be employed for the teaching of English, Japanese and Russian as foreign languages as well as for speech synthesis and recognition.