• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.418-427
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• 2016

A smart parking management requires to track a vehicle in a indoor parking lot and to detect the place where the vehicle is parked. An advanced parking system watches all space of the parking lot with CCTV cameras. We can use these cameras for vehicles tracking and detection. In order to cover a wide area with a camera, a fisheye lens is used. In this case the shape and size of an moving vehicle vary much with distance and angle to the camera. This makes vehicle detection and tracking difficult. In addition to the fisheye lens, the vehicle headlights also makes vehicle detection and tracking difficult. This paper describes a method of realtime vehicle detection and tracking robust to the harsh situation described above. In each image frame, we update the region of a vehicle and estimate the vehicle movement. First we approximate the shape of a car with a quadrangle and estimate the four sides of the car using multiple histograms of oriented gradient. Second we create a template by applying a distance transform to the car region and estimate the motion of the car with a template matching method.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.442-449
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• 2004

As underwater robotic vehicles (URVs) become attractive for more sophisticated underwater tasks, the demand of high performance in terms of accuracy and dexterity has been increased. An autonomous underwater robotic vehicle, ODIN (Omni-Directional Intelligent Navigator) was designed and built at the Autonomous Systems Laboratory of the University of Hawaii in 1991. Since 1991, various studies were conducted on ODIN and have contributed to the advancement in underwater robotics. Its refurbished model ODIN II was based on VxWorks in VMEbus. Recently, ODIN was born again as a PC based system, ODIN III with unique features such as new vehicle system software architecture with an objective-oriented concept, a graphical user interface, and an independent and modular structure using a Dynamic Linking Library (DLL) based on the Windows operating system. ODIN III software architecture offers an ideal environment where various studies for advanced URV technology can be conducted. This paper describes software architecture of ODIN III and presents initial experimental results of fine motion control on ODIN III.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.71-82
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• 2020

Traffic accidents due to excessive speed frequently occur in places where traffic signal controllers are installed, places where sharp curves exist, or places where the traffic signal cycle does not match the current time. These traffic accidents cause economic loss due to the destruction of road facilities and structures, and cause a big problem of increasing the number of traffic accident deaths. When a traffic accident occurs, leaving a tire mark before or after a car crash, pre-collision speed of the car is calculated using the law of conservation of momentum or the skid mark formula. In the skip skid mark generated in ABS brake vehicles and the combshaped yaw mark generated by tire trace caused by lateral sliding, there is a difference of 30-40% in the reliability of the vehicle speed calculated by the smite mark. In this paper, we propose an algorithm that can improve the calculation reliability in vehicle speed by using skid marks in order to compensate for this problem. In addition, we present an intelligent speed calculation algorithm for traffic safety and a computer simulation in order to prevent traffic accidents by estimating the speed of a vehicle, using Skid marks, Yaw marks, and ABS brake characteristics and fuzzy rules.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.313-321
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• 2017

One of the most frequently performed tasks in human-robot interaction (HRI), intelligent vehicles, and security systems is face related applications such as face recognition, facial expression recognition, driver state monitoring, and gaze estimation. In these applications, accurate head pose estimation is an important issue. However, conventional methods have been lacking in accuracy, robustness or processing speed in practical use. In this paper, we propose a novel method for estimating head pose with a monocular camera. The proposed algorithm is based on a deep neural network for multi-task learning using a small grayscale image. This network jointly detects multi-view faces and estimates head pose in hard environmental conditions such as illumination change and large pose change. The proposed framework quantitatively and qualitatively outperforms the state-of-the-art method with an average head pose mean error of less than $4.5^{\circ}$ in real-time.

• International Journal of Contents
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• v.14 no.1
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• pp.39-44
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• 2018

Today, cars have developed into intelligent automobiles that combine advanced control equipment and IT technology to provide driving assistance and convenience to users. These vehicles provide infotainment services to the driver, but this does not improve the safety of the driver. Accordingly, V2X communication, which forms a network between a vehicle and a vehicle, between a vehicle and an infrastructure, or between a vehicle and a human, is drawing attention. Therefore, various techniques for improving channel estimation performance without changing the IEEE 802.11p standard have been proposed, but they do not satisfy the packet error rate (PER) performance required by the C-ITS service. In this paper, we analyze existing channel estimation techniques and propose a new channel estimation scheme that achieves better performance than existing techniques. It does this by applying the updated matrix for the data pilot symbol to the construct data pilot (CDP) channel estimation scheme and by further performing the interpolation process in the frequency domain. Finally, through simulations based on the IEEE 802.11p standard, we confirmed the performance of the existing channel estimation schemes and the proposed channel estimation scheme by coded PER.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.135-140
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• 2020

The main battlefield of 'made in China 2025' proposed by the Chinese government is the deep integration of industrialization and informatization, among which intelligent manufacturing and new energy vehicles are the key links. New energy vehicle refers to the use of unconventional automotive fuel as a power source (or use conventional automotive fuel, the use of new vehicle-mounted power plant), integrated vehicle power control and driving aspects of advanced technology, the formation of advanced technical principles, with new technology and the structure of the vehicle. BYD's success in the battery, I T and automobile industries has attracted the attention of the industry, making it a shining new star in the Chinese business community. BYD 's innovation, diversification and corporate culture construction have certain enlightenment to the development of China's small and medium-sized enterprises. Therefore, by looking at the Chinese network literature, about BYD's research mainly focused on the development strategy, corporate finance, corporate performance, and corporate marketing, etc. This paper will take BYD as the research object and focus on corporate culture. Through literature analysis and qualitative analysis, it will summarize and further analyze the unique corporate culture of BYD, its important role, and provide relevant theoretical references for the construction and development of corporate culture in other industries.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.47-54
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• 2008

In order to realize Intelligent Transport System (ITS) without any road facilities support, Inter-vehicle Communication (IVC) is increased attention. IVC makes it possible to exchange real-time information among vehicles without centralized infrastructure. The IVC systems use multi-hop broadcast to disseminate information. In this paper, we propose the improved AODV routing protocol based on location information. The proposed AODV routing protocol transmits Hello packet with location information to calculate the distance between nodes. Then it achieves fast link recovery. We confirm the throughput performance of the proposed AODV routing protocol compared with the AODV routing protocol using Qualnet ver.3.8 simulator.

• Journal of Broadcast Engineering
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• v.24 no.7
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• pp.1266-1275
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• 2019

With increasing criminal rates and number of CCTVs, much attention has been paid to intelligent surveillance system on the horizon. Object detection and tracking algorithms have been developed to reduce false alarms and accurately help security agents immediately response to undesirable changes in video clips such as crimes and accidents. Many studies have proposed a variety of algorithms to improve accuracy of detecting and tracking objects outside tunnels. The proposed methods might not work well in a tunnel because of low illuminance significantly susceptible to tail and warning lights of driving vehicles. The detection performance has rarely been tested against the tunnel environment. This study investigated a feasibility of object detection and tracking in an actual tunnel environment by utilizing YOLOv3 and Kernelized Correlation Filter. We tested 40 actual video clips to differentiate pedestrians and motorcycles to evaluate the performance of our algorithm. The experimental results showed significant difference in detection between pedestrians and motorcycles without false positive rates. Our findings are expected to provide a stepping stone of developing efficient detection algorithms suitable for tunnel environment and encouraging other researchers to glean reliable tracking data for smarter and safer City.

• Journal of Multimedia Information System
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• v.3 no.4
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• pp.119-128
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• 2016

This study aims to suggest a new algorithm for detecting two-wheelers on road that have various shapes according to the viewing angle for vision based intelligent vehicles. This article describes a new approach to two-wheelers detection algorithm riding on people based on modified Histogram of Oriented Gradients (HOG) using correlation coefficient (CC). The CC between two local area variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using HOG which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the CC between the area of each cell and one of two-wheelers, can be extracted as the weighting factor in process for normalizing the modified HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.453-464
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• 2012

This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.