• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.2
• /
• pp.20-32
• /
• 2010

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.

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

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.6
• /
• pp.44-56
• /
• 2008

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2372-2374
• /
• 2003

With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. The first establishes reference points in space, and the second uses a grid type frame and statistical method. But, the former has difficulty to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. It can easily estimate camera calibration parameters such as focal length, scale factor, pose, orientations, and distance. But, radial lens distortion is not modeled. The advantage of this algorithm is that it can estimate the distance of the object. Also, the proposed camera calibration method is possible estimate distance in dynamic environment such as autonomous navigation. To validate proposed method, we set up the experiments with a frame on rotator at a distance of 1,2,3,4[m] from camera and rotate the frame from -60 to 60 degrees. Both computer simulation and real data have been used to test the proposed method and very good results have been obtained. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use.

• Korean Journal of Applied Biomechanics
• /
• v.20 no.4
• /
• pp.381-386
• /
• 2010

This study examined the changes in the walking pattern during level walking under low illumination conditions. Fourteen male subjects ($22.1{\pm}2.21$ years, $174{\pm}3.74\;cm$, $68.86{\pm}10.81\;kg$) with normal vision and no disabilities were enrolled in this study. All experiments were performed on a level walkway with three conditions: normal walking (preferred & low speed) and walking with low illumination. 3D motion capturing system was used for acquisition and analysis of the walking motion data with a sampling frequency of 120Hz. The walking speed, normalized jerk(NJ) at the center of mass(COM), wrist and heel, knee and elbow joint angle, ratio of the knee joint angle to elbow joint angle and the toe clearance on stance phase were used to compare the differences in walking pattern between the two illumination conditions, The results showed that the walking speed and joint angles decreased in low illumination, whereas the NJ and toe minimum clearance increased. In low illumination, most variables were similar to effects of low speed walking, but toe clearance was different from the effects of low speed. These results can be used as primary data for examining the changes in the level walking pattern of young adults under low illumination. Further study will be needed to compare these results in young adults with those in the elderly.

• The Journal of the Korea Contents Association
• /
• v.21 no.8
• /
• pp.1-9
• /
• 2021

Deep learning in computer vision has made accelerated improvement over a short period but large-scale learning data and computing power are still essential that required time-consuming trial and error tasks are involved to derive an optimal network model. In this study, we propose a similar image classification performance improvement method based on CR (Confusion Rate) that considers only the characteristics of the data itself regardless of network optimization or data reinforcement. The proposed method is a technique that improves the performance of the deep learning model by calculating the CRs for images in a dataset with similar characteristics and reflecting it in the weight of the Loss Function. Also, the CR-based recognition method is advantageous for image identification with high similarity because it enables image recognition in consideration of similarity between classes. As a result of applying the proposed method to the Resnet18 model, it showed a performance improvement of 0.22% in HanDB and 3.38% in Animal-10N. The proposed method is expected to be the basis for artificial intelligence research using noisy labeled data accompanying large-scale learning data.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.16 no.3
• /
• pp.54-67
• /
• 2013

This study deals with the characteristics of view landscape in modern Daegu city which were analysed employing geographic information system(GIS). The view landscape analysis was performed by using GIS that enables to overlap land use map with the map of range of visibility, and the 3-D simulation. The results are as follows; First of all, the ratio of forest is enormously high in the range of visibility. The distribution of landscape components allows the dwellers to obtain a clear view towards forests from anywhere. The landscape components include west eroded lowlands, east open rolling lands, east eroded lowlands, and high mountain areas: Apsan(Mt.) in the south; Waryoungsan(Mt.) in the west; and Hamjisan(Mt.) and Hakbong(Mt.) in the north. On the tops of those, people are able to secure a clear vision from the viewpoint towards the surrounding mountains because of the rural areas continuing from the viewpoint to the mountains. A continuous view landscape has been formed by these natural environmental factors. Finally, there are multiple view targets with relatively high altitude that are covered with forests in the space between the urban area and the outer mountains that are higher than the view targets, which provides a scenery of mountains overlapped by higher mountains.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.5
• /
• pp.211-220
• /
• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• Journal of Korean Ophthalmic Optics Society
• /
• v.10 no.2
• /
• pp.103-110
• /
• 2005

Binocular vision had a short history in Korea. As there were many near works in these days, the needs about comparative study have been increased. There was related to both refractive error and binocular anomalies, but it is difficult to applying for binocular vision expected findings in itself due to the fact that Korean differ from foreigner. Objects were 100 adults in 18-36 years old ages, The test was Von Gaefe method and used aparatus was phoropter(Shinnippon VT10)and visual chart(Shinnippon CT30). According to interview results was that symptom in near works were headaches 28.0%, blinking 27.3%, red eye 25.1%, eyepain 15.6%, watering 15.3%, itch 12.2%, photophobia 8.5% and eye strain 7.4%. A people who have above ${\pm}0.50$ D refractive error in total objectives (100-male 45/female 55) were classified into ametropia. There was a results such as emmetropia (12.0%), ametropia(88.0%), exophoria(32.0%), esophoria(12.0%). Far negative relative convergence were that in case of high 43.0%, in case of low 7.0%. Far positive relative convergence were that in case of high 15.0%, in case of low 38.0%. Near phoria was exophoria(32.0%), esophoria(12.0%). Near negative relative convergence were that in case of high 23.0%, in case of low 38.0%. Far positive relative convergence were that in case of high 29.0%, in case of low 23.0%. Near negative relative accommodation were that in case of high 10.0%, in case of low 14,0%, Far positive relative convergence were that in case of high 69.0%, in case of low 12.0%. Results were different from expected findings, and especially positive relative accommodation was very high, However, We suggest that the expected findings in Korea for several subjects must study in binocular function.

• Journal for History of Mathematics
• /
• v.20 no.3
• /
• pp.127-146
• /
• 2007

From 1876 to 1883, British mathematician James Joseph Sylvester worked as the founding head of Mathematics Department at the Johns Hopkins University which has been known as America's first school of mathematical research. Sylvester established the American Journal of Mathematics, the first sustained mathematics research journal in the United States. It is natural that we think this is the most exciting and important period in American mathematics. But we found out that the International Congress of Mathematicians held at the World's Columbian Exposition in Chicago, August 21-26, 1893 was the real turning point in American's dedication to mathematical research. The University of Chicago was founded in 1890 by the American Baptist Education Society and John D. Rockefeller. The founding head of mathematics department Eliakim Hastings Moore was the one who produced many excellent American mathematics Ph.D's in early stage. Many of Moore's students contributed to build up real American mathematics research power in early 20 century The University also has a well-deserved reputation as the "teacher of teachers". Beginning with Sylvester, we analyze what E.H. Moore had done as a teacher and a head of the new department that produced many mathematical talents such as L.E. Dickson(1896), H. Slaught(1898), O. Veblen(1903), R.L. Moore(1905), G.D. Birkhoff(1907), T.H. Hilderbrants(1910), E.W. Chittenden(1912) who made the history of American mathematics. In this article, we study how Moore's vision, new system and new way of teaching influenced American mathematical society at early stage of the top class mathematical research. and the meaning that early University of Chicago case gave.