• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.3
• /
• pp.209-218
• /
• 2013

Early researches in human action recognition have focused on tracking and classifying articulated body motions. Such methods required accurate segmentation of body parts, which is a sticky task, particularly under realistic imaging conditions. Recent trends of work have become popular towards the use of more and low-level appearance features such as spatio-temporal interest points. Given the great progress in pose estimation over the past few years, redefined views about pose-based approach are needed. This paper addresses the issues of whether it is sufficient to train a classifier only on low-level appearance features in appearance approach and proposes effective pose-based approach with pose estimation for emotional action recognition. In order for these questions to be solved, we compare the performance of pose-based, appearance-based and its combination-based features respectively with respect to scenario of various emotional action recognition. The experiment results show that pose-based features outperform low-level appearance-based approach of features, even when heavily spoiled by noise, suggesting that pose-based approach with pose estimation is beneficial for the emotional action recognition.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.4 no.1
• /
• pp.31-36
• /
• 2002

Peptidohlycan recognition protein (PGRP) is one of the pattern recognition proteins in innate immunity of insect. We isolated differentially expressed two cDNAa, BTL-LPI and BTL-LP2, in the fat body of Bombyx mori larvae injected with bacteria by subtractive hybridization method. These two clones showed amino acid sequence divergence of 30.4%. In the comparison with other insect PGRP genes, BTL-LP2 showed 48.8% and 45.2% of sequence homology to the known PGRP genes of Bombyx mori and Tricoplusia ni, respectively, and BTL-LP2 was 31.8% and 30.9% , respectively. Phylogenetic analysis showed relatively close relationship of the BTL-LP2 to the known insect PGRP, unlike BTL-LPI, which was equidistant both to insect and mammals, suggesting a divergent relationships of the two newly cloned B. mori PGRP genes. Northern blot analyses confirmed an induction of the expression of BTL-LP2 by the bacterial infection in the Int body of B. mori, suggesting the involvement of the gene in the insect immunity.

• Journal of Computing Science and Engineering
• /
• v.9 no.1
• /
• pp.29-38
• /
• 2015

Human action recognition has become an important research topic in computer vision area recently due to many applications in the real world, such as video surveillance, video retrieval, video analysis, and human-computer interaction. The goal of this paper is to evaluate descriptors which have recently been used in action recognition, namely Histogram of Oriented Gradient (HOG) and Histogram of Optical Flow (HOF). This paper also proposes new descriptors to represent the change of points within each part of a human body, caused by actions named as Histogram of Changing Points (HCP) and so-called Average Speed (AS) which measures the average speed of actions. The descriptors are combined to build a strong descriptor to represent human actions by modeling the information about appearance, local motion, and changes on each part of the body, as well as motion speed. The effectiveness of these new descriptors is evaluated in the experiments on KTH and Hollywood datasets.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.1264-1274
• /
• 2015

Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.

• Health Policy and Management
• /
• v.20 no.3
• /
• pp.157-172
• /
• 2010

This study was conducted to evaluate the effects of health-behavioral change for the elderly group after community based education of chronic diseases management. We measured self recognition of health status, medication administration of hypertension and diabetes, regular check for blood pressure and blood sugar level, recognition of body indicators (weight, hight, blood pressure, blood sugar etc), knowledge level for chronic diseases management and smoking and alcohol habitation before and after education of chronic diseases management for participants. The subjects of this study consist of 432 people with community-dwelling Seoul citizen being active churches. Education programs designed essential parts of fundamental chronic diseases management, physical exercises for health promotion, diet and nutrition etc. All data collection completed for 5 months from Aug. 2008 to Dec. 2008 by trained surveyors via interview survey. The data obtained were analyzed using descriptive statistics, Wilcoxon Singed Rank test, McNemar test and Paired t-test. The results showed that self recognition of health status, knowledge level for chronic diseases management, recognition of body indicators were statistically significantly increased after the education of chronic diseases management. Also, blood pressure were statistically significantly decreased in elderly with hypertension and blood sugar were statistically significantly decreased in elderly of high-risk group. Based on these results, it was suggested that preventive education policy of chronic diseases management should be considered with priority coming true for successful aging society.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.11
• /
• pp.2275-2280
• /
• 2009

u-Healthcare service is one of attractive applications in ubiquitous environment. In this paper, we propose a method to recognize exercises using a new accelerometer based body-attached platform for supporting u-Healthcare service. The platform consists of a device for measuring accelerometer data and a device for receiving the data. The former measures a user's motion data using a 3-axis accelerometer. The latter transmits the accelerometer data to a computer for recognizing the user's exercise. The algorithm for exercise recognition classifies the type of exercise using principle components analysis(PCA) from the accelerometer data transformed by discrete fourier transform(DFT), and estimates the repetition count of the recognized exercise using a peak detection algorithm. We evaluate the performance of the algorithm from the accuracy of the recognition of exercise type and the error rate of the estimation of repetition count. In our experimental result, the algorithm shows the accuracy about 98%.

• The Journal of the Korea Contents Association
• /
• v.18 no.12
• /
• pp.383-393
• /
• 2018

The purpose of this paper is to study on the elements of the Sinmyung and the expression recognition of body movement in Korean dance of college students majoring in musical. The participants were 12 male and female college students in musical major who experienced in dance, song and acting. The program was composed of the experience of the Sinmyung: recognition of sound and dance, breathing and movement in the Korean dance, 8 hours twice a week for four weeks. As a qualitative approach is the discovery of the center of the process, we carried out an inductive analysis of the area on the basis of observation, in-depth interview and student report. The core of this analysis is to attempt to analyze contents concentrating on the recognition exploration of the Sinmyung sentiment and the body expression through sound and breathing. In conclusion, for college students majoring in musical, the expression recognition of the experience of the Sinmyung and the movement in the Korean dance contributes to the improvement of creative thinking through body perception, and the practical use of the capacity of image expression through concentration of sound and breathing. Finally, the results of this research could articulate with the value of body expression and the creative factors of college students majoring in musical.

• Journal of Korea Multimedia Society
• /
• v.21 no.12
• /
• pp.1473-1480
• /
• 2018

The extraction and recognition of human motion characteristics need to combine biometrics to determine and judge human behavior in the movement and distinguish individual identities. The so-called biometric technology, the specific operation is the use of the body's inherent biological characteristics of individual identity authentication, the most noteworthy feature is the invariance and uniqueness. In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition. And we will use the KTH database to train and test the recognition system. Experiments have been very desirable results.

• International Journal of Computer Science & Network Security
• /
• v.22 no.1
• /
• pp.129-138
• /
• 2022

With the increasing reliance of computing systems in our everyday life, there is always a constant need to improve the ways users can interact with such systems in a more natural, effective, and convenient way. In the initial computing revolution, the interaction between the humans and machines have been limited. The machines were not necessarily meant to be intelligent. This begged for the need to develop systems that could automatically identify and interpret our actions. Automatic gesture recognition is one of the popular methods users can control systems with their gestures. This includes various kinds of tracking including the whole body, hands, head, face, etc. We also touch upon a different line of work including Brain-Computer Interface (BCI), Electromyography (EMG) as potential additions to the gesture recognition regime. In this work, we present an overview of several applications of automated gesture recognition systems and a brief look at the popular methods employed.

• International journal of advanced smart convergence
• /
• v.6 no.3
• /
• pp.29-37
• /
• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.