• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.9-20
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• 2014

Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.463-476
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• 2022

In this paper, we propose a table tennis posture classification system using a cooperative robot to develop a table tennis robot that can be trained like a real game. The most ideal table tennis robot would be a robot with a high joint driving speed and a high degree of freedom. Therefore, in this paper, we intend to use a cooperative robot with sufficient degrees of freedom to develop a robot that can be trained like a real game. However, cooperative robots have the disadvantage of slow joint driving speed. These shortcomings are expected to be overcome through quick recognition. Therefore, in this paper, we try to quickly classify the opponent's posture to overcome the slow joint driving speed. To this end, learning about dynamic postures was conducted using image data as input, and finally, three classification models were created and comparative experiments and evaluations were performed on the designated dynamic postures. In conclusion, comparative experimental data demonstrate the highest classification accuracy and fastest classification speed in classification models using MLP (Multi-Layer Perceptron), and thus demonstrate the validity of the proposed algorithm.

• Smart Media Journal
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• v.9 no.4
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• pp.102-108
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• 2020

In this paper, we propose a real-time method of detecting hand motions and extracting the signal frame induced by EF(Electric Field) sensors. The signal induced by hand motion includes not only noises caused by various environmental sources as well as sensor's physical placement, but also different initial off-set conditions. Thus, it has been considered as a challenging problem to detect the motion signal and extract the motion frame automatically in real-time. In this study, we remove the PLN(Power Line Noise) using LPF with 10Hz cut-off and successively apply MA(Moving Average) filter to obtain clean and smooth input motion signals. To sense a hand motion, we use two thresholds(positive and negative thresholds) with offset value to detect a starting as well as an ending moment of the motion. Using this approach, we can achieve the correct motion detection rate over 98%. Once the final motion frame is determined, the motion signals are normalized to be used in next process of classification or recognition stage such as LSTN deep neural networks. Our experiment and analysis show that our proposed methods produce better than 98% performance in correct motion detection rate as well as in frame-matching rate.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.281-289
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• 2000

While acquiring images, the relative motion between the imaging device and the object scene seriously damages the image quality. This phenomenon is called motion blur. The peak-trace approach, which is our recent previous work, identifies important parameters to characterize the point spread function (PSF) of the blur, given only the blurred image itself. With the peak-trace approach the direction of the motion blur can be extracted regardless of the noise corruption and does not need much Processing time. In this paper stochastic peak-trace approaches are introduced. The erroneous data can be selected through the ML classification, and can be made small through weighting. Therefore the distortion of the direction in the low frequency region can be prevented. Using the linear prediction method, the irregular data are prohibited from being selected as the peak point. The detection of the second peak using the proposed moving average least mean (MALM) method is used in the Identification of the motion extent. The MALM method itself includes a noise removal process, so it is possible to extract the parameters even an environment of heavy noise. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.120-127
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• 2008

Practical use degree of Motion Capture technology is low in korea game market which did growth of MMORPG putting first. However, that is dance game or FPS, sports game genre is magnified. Therefore, practical use degree of Motion Capture technology is increasing. And, need various research to take advantage of Motion Capture technology effectively. Studied 3D game character animation manufacture pipe line for it. Characteristic of this manufacture pipe line is work classification, correction of two times, Biped format all-in-one to progress Motion Capture technology and keyframe-animation work at the same time. Also, manufacture pipe line that is consisted of this constituent has economic performance, extensity, systemicity.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.621-625
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• 2010

This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2313-2326
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• 2018

The method of operating a game could determine the psychological distance between the player and the game character, and thus, in the Virtual Reality, players' control methodologies are important to enhance their immersion. This study has the objective of examining the difference in games according to the method of operation based on the player's movements. This study researched the effect of the method of operating movement conforming to the movement of the character and the physical operation of the body on forming game experiences for the player. The result of performing an experiment increased reality for the game player through a controller in the shape of the actual control, to increase focus in the game. As so, game play through movements, including actual movements by the player displayed to enhance game satisfaction. In the part of media remediation field, Game can be defined as media which has their own unique hypermediacy. Especially, in the motion based game, players' movement mediates players and the game, therefore, players' movement could make players' experience augmented or immediate in accordance with the characteristics of movements. Even though sports and dances genres of motion-based games are common, RPG or adventure genres are rare. It can be explained that the characteristics of the action have been explained in the immediacy. In a game of fantasy, which is difficult to experience in real-life situations, the nature of the player's motion can increase the immersion of the game, which can contribute to utilization of players' motion and experience design in the various genres and suggestion of grounds theory. In addition, through this study, it is able to design motion-based games of various genres.

• Clinics in Shoulder and Elbow
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• v.21 no.2
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• pp.82-86
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• 2018

Background: Although a common shoulder disease, there are no accepted classification criteria for frozen shoulder (FS). This study therefore aimed to evaluate the accuracy of the conventionally used FS classification system. Methods: Primary FS patients (n=168) who visited our clinic from January 2010 to July 2015 were included in the study. After confirming restrictions of the glenohumeral joint motion and absence of history of systemic disease, trauma, shoulder surgery, shoulder muscle weakness, or specific x-ray abnormalities, the Zuckerman and Rokito's classification was employed for diagnosing primary FS. Following clinical diagnosis, each patient underwent a shoulder magnetic resonance imaging (MRI) and blood tests (lipid profile, glucose, hemoglobin A1c, and thyroid function). Based on the results of the blood tests and MRIs, the patients were reclassified, using the criteria proposed by Zuckerman and Rokito. Results: New diagnoses were ascertained including blood test results (16 patients with diabetes, 43 with thyroid abnormalities, and 149 with dyslipidemia), and MRI revealed intra-articular lesions in 81 patients (48.2%). After re-categorization based on the above findings, only 5 patients (3.0%) were classified having primary FS. The remaining 163 patients (97.0%) had either undiagnosed systemic or intrinsic abnormalities (89 patients), whereas 74 patients had both. Conclusions: These findings demonstrate that most patients clinically diagnosed with primary FS had undiagnosed systemic abnormalities and/or intra-articular pathologies. Therefore, a modification of the Zuckerman and Rokito's classification system for FS may be required to include the frequent combinations, rather than having a separate representation of systemic abnormalities and intrinsic causes.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.171-181
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• 2012

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.

• The Journal of the Korea Contents Association
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• v.7 no.8
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• pp.102-108
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• 2007

Among culture industry that greet digital generation and is observed 21th century the most representative game industry latest is caught what and more interest degree is rising. 2D and 3D animation accomplish continuous growth and development depending action expression along with development of computer technology, and 2D and 3D animation practical use extent are trend that is widening the area in TV, movie, GAME industry etc. through computer hardware and fast change of software technology. The trend of latest game graphic is trend that the weight is changing from 2D to 3D by 3D game and activation of 3D game character that raise player's immersion stuff and Control in 2D's simplicity manufacturing game balance for one side. This treatise that is reality of 3D game character to classify kind of (Motion Capture) and 3D character animation, form model the sense put. Recognize that is overview and reality of 3D game character first for this about example, and is considered to efficiency is high game industry and digital contents industry hereafter by proposing kind model classification of 3D game character animation, form model classification data and character animation manufacture process that application is possible at fast time and effect in 3D character animation application are big.