• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.04a
• /
• pp.397-400
• /
• 2007

In this paper, we discuss the user-customized interaction for intelligent home environments. The interactive system is based upon the integrated techniques using both speech and face recognition. For essential modules, the speech recognition and synthesis were basically used for a virtual interaction between user and proposed system. In experiments, particularly, the real-time speech recognizer based on the HM-Net(Hidden Markov Network) was incorporated into the integrated system. Besides, the face identification was adopted to customize home environments for a specific user. In evaluation, the results showed that the proposed system was easy to use for intelligent home environments, even though the performance of the speech recognizer did not show a satisfactory results owing to the noisy environments.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.4
• /
• pp.1657-1662
• /
• 2017

Facial expression recognition systems using video devices have emerged as an important component of natural human-machine interfaces which contribute to various practical applications such as security systems, behavioral science and clinical practices. In this work, we present a new method to analyze, represent and recognize human facial expressions using a sequence of facial images. Under our proposed facial expression recognition framework, the overall procedure includes: accurate face detection to remove background and noise effects from the raw image sequences and align each image using vertex mask generation. Furthermore, these features are reduced by principal component analysis. Finally, these augmented features are trained and tested using Hidden Markov Model (HMM). The experimental evaluation demonstrated the proposed approach over two public datasets such as Cohn-Kanade and AT&T datasets of facial expression videos that achieved expression recognition results as 96.75% and 96.92%. Besides, the recognition results show the superiority of the proposed approach over the state of the art methods.

• Journal of Internet Computing and Services
• /
• v.3 no.4
• /
• pp.51-59
• /
• 2002

For the speech recognition, this paper proposes a improved new formant tracking algorithm The recognition data for the simulation on this paper are used with the Korean digit speech. The recognition rate of the improved algorithm for the Korean digit speech shows 91% for 300 digit speech The effectiveness of this research has been confirmed through recognition simulations.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.961-968
• /
• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.20 no.4
• /
• pp.1309-1319
• /
• 1996

The research for the classification of the natural defects in welding zone is performd using the neuro-pattern recognition technology. The signal pattern recognition package including the user's defined function is developed to perform the digital signal processing, feature extraction, feature selection and classifier selection, The neural network classifier and the statistical classifiers such as the linear discriminant function classifier and the empirical Bayesian calssifier are compared and discussed. The neuro-pattern recognition technique is applied to the classificaiton of such natural defects as root crack, incomplete penetration, lack of fusion, slag inclusion, porosity, etc. If appropriately learned, the neural network classifier is concluded to be better than the statistical classifiers in the classification of the natural welding defects.

• Journal of Information Processing Systems
• /
• v.19 no.3
• /
• pp.323-333
• /
• 2023

Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.49 no.2
• /
• pp.61-74
• /
• 2012

In this paper, we propose a illumination-robust face recognition system using MCS-LBP and 2D-PCA algorithm. A binary pattern transform which has been used in the field of the face recognition and facial expression, has a characteristic of robust to illumination. Thus, this paper propose MCS-LBP which is more robust to illumination than previous LBP, and face recognition system fusing 2D-PCA algorithm. The performance evaluation of proposed system was performed by using various binary pattern images and well-known face recognition features such as PCA, LDA, 2D-PCA and ULBP histogram of gabor images. In the process of performance evaluation, we used a YaleB face database, an extended YaleB face database, and a CMU-PIE face database that are constructed under varying lighting condition, and the proposed system which consists of MCS-LBP image and 2D-PCA feature show the best recognition accuracy.

• Korean Institute of Interior Design Journal
• /
• v.14 no.4 s.51
• /
• pp.122-133
• /
• 2005

This study could begin with the improvement of computer graphic technology The graphic technology is the standards of computer technology level and up-to-date technology intensive. Above all, the technology of virtual reality has developed rapidly and the development of the program has changed from professional one only for the experts to easy of access ones for the space designers. Moreover, the program which major internet user's can experience the virtual model has been made, as the development of virtual reality technology that is based on the web. These graphic technology and the development of the web helped to extract human experiences on the space design step. However, to find the meeting point with real recognition is not easy though the virtual reality technology develops. Because the real space is made up of various senses that people feel in their surroundings. But, this study was possible because most of the space recognition is based on the visual organ, even though it can't satisfy all sensible factors that we feel in reality. Therefore, the significant of this study is the standards and criteria of evaluation, the technological proposal, expecting to make more advanced alternative design than before.

• Korean Institute of Interior Design Journal
• /
• v.22 no.6
• /
• pp.119-129
• /
• 2013

For commercial inner space, studies about brand communication and VMD to inform brand identity to customers are very important. Accordingly, the study conducted questionnaire survey about 'emotional reaction, brand recognition, brand communication and satisfaction on VMD expressional elements' of customers and brand-related personnel on the ZARA flagship store. Through analysis of difference of evaluation on surveyed items between customers and brand personnels, importance of direction of VMD design applying brand communication which can satisfy customers and application of brand communication was verified. Specific results of the research are as follows: First, comparing brand personnel's expectation of recognition of their brand from customers, substantial level of recognition of brand by customers was lower. It is necessary for improvement through consumer analysis in order to raise brand recognition. Second, as the result of analysis of emotional reaction on VMD, it needs to lead customers to positive emotional reaction close to the brand plan intention by inducing 'exciting and sensational' brand concept to emotional reactions through comprehensive VMD image management and leading to 'free and convenient' emotional reaction and then communications with customers and minimizing emotional differences. Third, for brand communication and creation of 'interest', intention of ZARA, it needs to get maximum communicative effects with 'young' VMD design. Fourth, for satisfaction survey on VMD expressional elements, customers was less satisfied than brand personnel. Accordingly, in order to raise customers' satisfaction, show windows, entry, mannequins and objets should be planned with priority and it should also satisfy customers through communications with customers including advertisement and marketing.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.5 no.4
• /
• pp.363-371
• /
• 2010

In an effort to enhance the quality of feature vector classification and thereby reduce the recognition error rate for the speaker-independent speech recognition, we study the effect of spectral tilt on the Fourier magnitude spectrum en route to the extraction of MFCC. The effect of FIR filtering on the speech signal on the speech recognition is also investigated in parallel. Evaluation of the proposed methods are performed by two independent ways of the Fisher discriminant objective function and speech recognition test by hidden Markov model with fuzzy vector quantization. From the experiments, the recognition error rate is found to show about 10% relative improvements over the conventional method by an appropriate choice of the tilt factor.