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.
Kim, Sukhyun;Lee, Jinsung;Yu, Eunsang;Park, Seon-u;Kim, Eung-Tae
Proceedings of the Korean Society of Broadcast Engineers Conference
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fall
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pp.290-293
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2021
In this paper, we implement a learning efficiency verification system to inspire learning motivation and help improve concentration by detecting the situation of the user studying. To this aim, data on learning attitude and concentration are measured by extracting the movement of the user's face or body through a real-time camera. The Jetson board was used to implement the real-time embedded system, and a convolutional neural network (CNN) was implemented for image recognition. After detecting the feature part of the object using a CNN, motion detection is performed. The captured image is shown in a GUI written in PYQT5, and data is collected by sending push messages when each of the actions is obstructed. In addition, each function can be executed on the main screen made with the GUI, and functions such as a statistical graph that calculates the collected data, To do list, and white noise are performed. Through learning efficiency checking system, various functions including data collection and analysis of targets were provided to users.
The Journal of the Korea institute of electronic communication sciences
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v.19
no.1
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pp.217-224
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2024
With the rapid growth of K-POP, the dance content industry is spreading. With the recent increase in the spread of SNS, they also shoot and share their dance videos. However, it is not easy for dance beginners who are new to dancing to learn dance moves because it is difficult to receive objective feedback when dancing alone while watching videos. This paper describes a system that uses MediaPipe to compare choreography videos and dance videos of users and detect whether they are following the movement correctly. This study proposes a method of giving feedback based on Color Map to users by calculating the similarity of dance movements between user images taken with webcam or camera and choreography images using cosine similarity and COCO OKS. Through this system, objective feedback on users' dance movements can be visually received, and beginners are expected to be able to learn accurate dance movements.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2022.05a
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pp.165-167
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2022
The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.
The Journal of Korean Institute of Communications and Information Sciences
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v.32
no.2C
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pp.141-149
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2007
Associating the shoulder line with head location of the human body is useful in verifying, localizing and tracking persons in an image. Since the head line and the shoulder line, what we call ${\Omega}$-shape, move together in a consistent way within a limited range of deformation, we can build a statistical shape model using Active Shape Model (ASM). However, when the conventional ASM is applied to ${\Omega}$-shape fitting, it is very sensitive to background edges and clutter because it relies only on the local edge or gradient. Even though appearance is a good alternative feature for matching the target object to image, it is difficult to learn the appearance of the ${\Omega}$-shape because of the significant difference between people's skin, hair and clothes, and because appearance does not remain the same throughout the entire video. Therefore, instead of teaming appearance or updating appearance as it changes, we model the discriminative appearance where each pixel is classified into head, torso and background classes, and update the classifier to obtain the appropriate discriminative appearance in the current frame. Accordingly, we make use of two features in fitting ${\Omega}$-shape, edge gradient which is used for localization, and discriminative appearance which contributes to stability of the tracker. The simulation results show that the proposed method is very robust to pose change, occlusion, and illumination change in tracking the head and shoulder line of people. Another advantage is that the proposed method operates in real time.
Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.
The Journal of the Convergence on Culture Technology
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v.7
no.3
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pp.577-582
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2021
Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences
Journal of the Korea Society of Computer and Information
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v.29
no.2
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pp.31-41
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2024
Deep learning models show excellent performance in tasks such as image classification and object detection in the field of computer vision, and are used in various ways in actual industrial sites. Recently, research on improving robustness has been actively conducted, along with pointing out that this deep learning model is vulnerable to hostile examples. A hostile example is an image in which small noise is added to induce misclassification, and can pose a significant threat when applying a deep learning model to a real environment. In this paper, we tried to confirm the robustness of the edge-learning classification model and the performance of the adversarial example detection model using it for adversarial examples of various algorithms. As a result of robustness experiments, the basic classification model showed about 17% accuracy for the FGSM algorithm, while the edge-learning models maintained accuracy in the 60-70% range, and the basic classification model showed accuracy in the 0-1% range for the PGD/DeepFool/CW algorithm, while the edge-learning models maintained accuracy in 80-90%. As a result of the adversarial example detection experiment, a high detection rate of 91-95% was confirmed for all algorithms of FGSM/PGD/DeepFool/CW. By presenting the possibility of defending against various hostile algorithms through this study, it is expected to improve the safety and reliability of deep learning models in various industries using computer vision.
After its experiment involving the exploding of a satellite in space in 2007, China proudly aired news on TV and ran articles in newspapers. However, the event was internationally criticized and drew widespread attention. Many countries denounced the explosion by pointing out that it could be part of the nation's plan to expand its military power to space or that it could pose a danger to the peaceful use of space. However, there is no talk of whether the experiment that produced a huge amount of space debris could have violated an international law, namely the Outer Space Treaty. Although space garbage has been said to be a serious problem, the amount is still on the increase. If we continue to launch new space launch vehicles into orbit at this rate, we will not be able to use it anytime soon like we do today. As the commercial use of space is likely to increase, the situation will certainly get worse. The international community is fully aware of the seriousness of the problem and working together to reduce the amount of space garbage. However, despite the fact that the United States and Soviet Union's ASAT(Anti-Satellite) programs have been implemented for a long time, there have been no complaints about them in terms of military expansion or breach of the Outer Space Treaty. Also, the recent Chinese test is largely viewed to be in accordance with international law. A lot of research has been undertaken with regard to the problem of space garbage. Now people's awareness of dangers being posed has been fully raised. Under the circumstances, the dismissing of China's satellite smashing, leaving a big mess in its wake, as nothing more than an experiment, is a red flag to, if not many, at least some people. By means of this thesis, I would like to review whether the Chinese test has violated an international space law. This thesis presents an overview of the issues surrounding the event and examines the possibility of violating the Outer Space Treaty, formally the Treaty on Principle Governing the Activities of States in the Exploration and Use of Outer Space, Including the Moon and Other Celestial Bodies. After the China test, the UN Scientific and Technical Subcommittee first adopted space debris mitigation guidelines, I'll introduce the content of the guidelines and discuss the characteristics of the guidelines and what can be done to address the issue.
International circulation of cultural assets involves numerous countries thereby making an approach based on international law essential to resolving this problem. Since the end of the $2^{nd}$ World War, as the value of cultural assets evolved from material value to moral and ethical values, with emphasis on establishing national identities, newly independent nations and former colonial states took issue with ownership of cultural assets which led to the need for international cooperation and statutory provisions for the return of cultural assets. UNESCO's 1954 "Convention for the Protection of Cultural Property in the Event of Armed Conflict" as preparatory measures for the protection of cultural assets, the 1970 "Convention on the Means of Prohibiting and Preventing the Illicit Import and Transfer of Ownership of Cultural Property" to regulate transfer of cultural assets, and the 1995 "Unidroit Convention on Stolen or Illegally Exported Cultural Objects" which required the return of illegally acquired cultural property are examples of international agreements established on illegal transfers of cultural assets. In addition, the UN agency UNESCO established the Division of Cultural Heritage to oversee cultural assets related matters, and the UN since its 1973 resolution 3187, has continued to demonstrate interest in protection of cultural assets. The resolution 3187 affirms the return of cultural assets to the country of origin, advises on preventing illegal transfers of works of art and cultural assets, advises cataloguing cultural assets within the respective countries and, conclusively, recommends becoming a member of UNESCO, composing a forum for international cooperation. Differences in defining cultural assets pose a limitation on international agreements. While the 1954 Convention states that cultural assets are not limited to movable property and includes immovable property, the 1970 Convention's objective of 'Prohibiting and preventing the illicit import, export and transfer of ownership of cultural property' effectively limits the subject to tangible movable cultural property. The 1995 Convention also has tangible movable cultural property as its subject. On this point, the two conventions demonstrate distinction from the 1954 Convention and the 1972 Convention that focuses on immovable cultural property and natural property. The disparity in defining cultural property is due to the object and purpose of the convention and does not reflect an inherent divergence. In the case of Korea, beginning with the 1866 French invasion, 36 years of Japanese colonial rule, military rule and period of economic development caused outflow of numerous cultural assets to foreign countries. Of course, it is neither possible nor necessary to have all of these cultural properties returned, but among those that have significant value in establishing cultural and historical identity or those that have been taken symbolically as a demonstration of occupational rule can cause issues in their return. In these cases, the 1954 Convention and the ratification of the first legislation must be actively considered. In the return of cultural property, if the illicit acquisition is the core issue, it is a simple matter of following the international accords, while if it rises to the level of diplomatic discussions, it will become a political issue. In that case, the country requesting the return must convince the counterpart country. Realizing a response to the earnest need for preventing illicit trading of cultural assets will require extensive national and civic societal efforts in the East Asian area to overcome its current deficiencies. The most effective way to prevent illicit trading of cultural property is rapid circulation of information between Interpol member countries, which will require development of an internet based communication system as well as more effective deployment of legislation to prevent trading of illicitly acquired cultural property, subscription to international conventions and cataloguing collections.
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