• Journal of Korea Game Society
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• v.9 no.1
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• pp.127-134
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• 2009

This paper presents a motion generation technique for arbitrary morphologies with the user defined correspondences between joints. Users can define the controlling part in the source character and the part to be controlled in the target character in our system. To remove the restriction in the morphology of the target character, we use the pair of example posture sets. In our system, in order to provide the correspondence regardless of the number of joints, the deformed part in the target character is simplified into the direction vector. The final postures are then generated with the weighted sum of the examples. Our experimental results demonstrate that our approach can generate motions for various target characters and can control the user defined joints in real-time.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.1-13
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• 2011

In this paper, we propose a gesture recognition system to recognize motions using the shape information of MHI (Motion History Image). The system acquires MHI to provide information on motions from images with input and extracts the gradient images from such MHI for each X and Y coordinate. It extracts the shape information by applying the shape context to each gradient image and uses the extracted pattern information values as the feature values. It recognizes motions by learning and classifying the obtained feature values with a SVM (Support Vector Machine) classifier. The suggested system is able to recognize the motions for multiple people as well as to recognize the direction of movements by using the shape information of MHI. In addition, it shows a high ratio of recognition with a simple method to extract features.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.175-182
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• 2005

This paper presents encryption techniques for digital right management solutions of MPEG-4 streams. MPEG-4 is a format for multimedia streaming and stored in the MPEG-4 file format. We designed three kinds of encryption methods, which encrypt macro blocks (MBs) or motion vectors (MVs) of I-, P-VOPs (Video Object Planes), extracted from the MPEG-4 file format. We used DES to encrypt MPEG-4 data Based on theses three methods, we designed and implemented a DRM solution for an Internet broadcasting service, which enabled a MPEG-4 data streaming, and then compared the results of decryption speed and quality of rendered video sequences to get an optimal encryption method.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.129-141
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• 2010

In this paper, we present a wearable intelligent device based on multi-sensor for monitoring human activity. In order to recognize multiple activities, we developed activity recognition algorithms utilizing an image sensor and a 3-axis accelerometer sensor. We proposed a grid?based optical flow method and used a SVM classifier to analyze data acquired from multi-sensor. We used the direction and the magnitude of motion vectors extracted from the image sensor. We computed the correlation between axes and the magnitude of the FFT with data extracted from the 3-axis accelerometer sensor. In the experimental results, we showed that the accuracy of activity recognition based on the only image sensor, the only 3-axis accelerometer sensor, and the proposed multi-sensor method was 55.57%, 89.97%, and 89.97% respectively.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.593-605
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• 2022

The purpose of this study is to investigate the personalized treacmill exercise analysis using a smart mirror based on Kinect sensor. To evaluate the performance of the development system, 10 health males were used to measure the range of the hip joint, knee joint, and ankle joint using a smart mirror when walking on a treadmill. For the validity and reliability of the development system, the validity and reliability were analyzed by comparing the human movement data measured by the Kinect sensor with the human movement data measured by the infrared motion capture device. As a result of validity verification, the correlation coefficient r=0.871~0.919 showed a high positive correlation, and through linear regression analysis, the validity of the smart mirror system was 88%. Reliability verification was conducted by ICC analysis. As a result of reliability verification, the correlation coefficient r=0.743~0.916 showed high correlation between subjects, and the consistency for repeated measurement was also very high at ICC=0.937. In conclusion, despite the disadvantage that Kinect sensor is less accurate than the motion capture system, Kinect is it has the advantage of low price and real-time information feedback. This means that the Kinect sensor is likely to be used as a tool for evaluating exercise prescription through human motion measurement and analysis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.105-114
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• 2011

The snake algorithm is widely adopted to track objects by extracting the active contour of the object from background. However, it fails to track the target converging to the background if there exists background whose gradient is greater than that of the pixels on the contour. Also, the contour may shrink when the target moves fast and the snake algorithm misses the boundary of the object in its searching window. To alleviate these problems, we propose an improved algorithm that can track object contour more robustly. Firstly, we propose two external energy functions, the edge energy and the contrast energy. One is designed to give more weight to the gradient on the boundary and the other to reflect the contrast difference between the object and background. Secondly, by computing the motion vector of the contour from the difference of the two consecutive frames, we can move the snake pointers of the previous frame near the region where the object boundary is probable at the current frame. Computer experiments show that the proposed method is more robust to the complicated background than the previously known methods and can track the object with fast movement.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.345-355
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• 2008

SIFT is popularly used in computer vision application such as object recognition, motion tracking, and 3D reconstruction among various shape descriptors. However, it is not easy to apply SIFT into the image similarity search as it is since it uses many high dimensional keypoint vectors. In this paper, we present a SIFT based image similarity search method using an edge image pyramid and an interesting region detection. The proposed method extracts keypoints, which is invariant to contrast, scale, and rotation of image, by using the edge image pyramid and removes many unnecessary keypoints from the image by using the hough transform. The proposed hough transform can detect objects of ellipse type so that it can be used to find interesting regions. Experimental results demonstrate that the retrieval performance of the proposed method is about 20% better than that of traditional SIFT in average recall.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.345-354
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• 2014

In this paper, we propose a real-time algorithm for estimating the relative position and velocity of a person with respect to a robot using a Kinect sensor and an extended Kalman filter (EKF). Additionally, we propose an algorithm for controlling the robot in the proximity of a person in a variety of modes. The algorithm detects the head and shoulder regions of the person using a histogram of oriented gradients (HOG) and a support vector machine (SVM). The EKF algorithm estimates the relative positions and velocities of the person with respect to the robot using data acquired by a Kinect sensor. We tested the various modes of proximity movement for a human in indoor situations. The accuracy of the algorithm was verified using a motion capture system.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.43-48
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• 2014

Usually, image deconvolution is applied as a preprocessing step in surveillance systems to reduce the effect of motion or out-of-focus blur problem. In this paper, we propose a blind-image deconvolution filtering approach based on genetic programming (GP). A numerical expression is developed using GP process for image restoration which optimally combines and exploits dependencies among features of the blurred image. In order to develop such function, first, a set of feature vectors is formed by considering a small neighborhood around each pixel. At second stage, the estimator is trained and developed through GP process that automatically selects and combines the useful feature information under a fitness criterion. The developed function is then applied to estimate the image pixel intensity of the degraded image. The performance of developed function is estimated using various degraded image sequences. Our comparative analysis highlights the effectiveness of the proposed filter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.185-188
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• 2017

Health promotion is essential for overcoming the low health longevity of senior citizens preparing for aging population. Therefore, the lower body strengthening exercise to prevent falls is crucial to prevent a fall in the number of deaths of senior citizens. In this game model, the elderly are aiming at home training contents that can be found to feel that the elderly are going out of walk and exercising in the natural environment. To achieve this, Kinect extracts a specific bone model provided by the Kinect Sensor to generate the feature vectors and recognizes the movements and motion of the user.