• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.413-414
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• 1998

This paper presents a real-time Spatial Decision Support System(SDSS) for security camera image monitoring. Other SDSSs are not real-time systems, i.e., they show the images that are already transformed into data format such as virtual reality. In our system, the image is broadcasted in real-time since the purpose of the security camera needs to do it in real-time. With these real-time images, other systems do not add up anything more; the screen just shows the images from the camera. However in our system, we created a motion detection system so that the supervisor(Judge) of a sec.urity monitoring system does not have to pay attention to it constantly. In other words, we created a judge advising system for the supervisor of the security monitoring system. Most of small objects do not need the supervisor's attention since they could be birds, cats, dogs, etc. if they show up in the screen image. In this new system the system only report the unusual change to the supervisor by calculating the motion and size of objects in the screen. Thus the supervisor can be liberated from the 24-hour concentration duty; instead he/she can be only alerted when the real security threat such as a big moving object like an human intruder appears. Thus this system can be called a real-time Spatial DSS. The utility of this system is proved mathematically by using the concept of entropy. In other words, big objects like human intruders increase the entropy of the screen images significantly therefore the supervisor must be alerted. Thus by proving its utility of the system theoretically, we can claim that our new real-time SDSS is superior to others which do not use our technique.hnique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.34-40
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• 2018

This paper presents a new method to estimate the pose of a moving object accurately using a monocular camera and a low-end GPS+IMU sensor system. For this goal, we adopted a deep neural network for the semantic segmentation of input images and compared the results with a semantic map of a neighborhood. In this map matching, we use weight tables to deal with label inconsistency effectively. Signals from a low-end GPS+IMU sensor system are used to limit search spaces and minimize the proposed function. For the evaluation, we added noise to the signals from a high-end GPS-IMU system. The results show that the pose can be recovered from the noisy signals. We also show that the proposed method is effective in handling non-open-sky situations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.38-48
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• 1996

We implemented and evaluated the preformance of a task level pipelined multicomputer "RV860-PIPE(Realtime Vision i860 system using PIPEline)" for computer vision applications. RV860-PIPE is a message-passing MIMD computer having ring interconnection network which is appropriate for vision processing. We designed the node computer of RV860-PIPE using a 64-bit microprocessor to have generality and high processing power for various vision algorithms. Furthermore, to reduce the communication overhead between node computers and between node computer and a frame grabber, we designed dedicated high speed communication channels between them. We showed the practical applicability of the implemented system by evaluting performances of various computer vision applications like edge detection, real-time moving object tracking, and real-time face recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.274-281
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• 2006

Sensor network applications need synchronized time extremely such as object tracking, consistent state updates, duplicate detection, and temporal order delivery. This paper describes reliable time synchronization protocol (RTSP) for wireless sensor networks. In the proposed method, synchronization error is decreased by creating hierarchical tree with lower depth and reliability is improved by maintaining and updating information of candidate parent nodes. The RTSP reduces recovery time and communication overheads comparing to TPSN when there are topology changes owing to moving of nodes, running out of energy and physical crashes. Simulation results show that RTSP has about 20% better performance than TPSN in synchronization accuracy. And the number of message in the RTSP is $20%{\sim}60%$ lower than that in the TPSN when nodes are failed in the network. In case of different transmission range of nodes, the communication overhead in the RTSP is reduced up to 40% than that in the TPSN at the maximum.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.1-7
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• 2005

This paper describes the system for detecting vehicles in the rear and rear-side that access between sidewalk and bus stopped to city road at day by computer vision-based method. This system informs appearance of vehicles to bus driver and passenger for the safety of a bus passenger getting off. The camera mounted on the top portion of the bus exit door gets the rear and rear-side image of the bus whenever a bus stops at the stop. The system sets search area between bus and sidewalk from this image and detects a vehicle by using change of image and sobel filtering in this area. From a central point of the vehicle detected, we can find out the distance, speed and direction by its location, width and length. It alarms the driver and passengers when it's judged that dangerous situation for the passenger getting off happens. This experiment results in a detection rate more than 87% in driving by bus on the road.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.30-38
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• 2006

In this paper, we improved to drops recognition rate according to distance using distance and depth information with 3D from stereo face images. A monocular face image has problem to drops recognition rate by uncertainty information such as distance of an object, size, moving, rotation, and depth. Also, if image information was not acquired such as rotation, illumination, and pose change for recognition, it has a very many fault. So, we wish to solve such problem. Proposed method consists of an eyes detection algorithm, analysis a pose of face, md principal component analysis (PCA). We also convert the YCbCr space from the RGB for detect with fast face in a limited region. We create multi-layered relative intensity map in face candidate region and decide whether it is face from facial geometry. It can acquire the depth information of distance, eyes, and mouth in stereo face images. Proposed method detects face according to scale, moving, and rotation by using distance and depth. We train by using PCA the detected left face and estimated direction difference. Simulation results with face recognition rate of 95.83% (100cm) in the front and 98.3% with the pose change were obtained successfully. Therefore, proposed method can be used to obtain high recognition rate with an appropriate scaling and pose change according to the distance.

• Smart Media Journal
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• v.9 no.4
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• pp.97-101
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• 2020

Using passive electric field sensor which operates in non-contact mode, we can measure the electric potential induced from the change of electric charges on a sensor caused by the movement of human body or hands. In this study, we propose a new method, which utilizes PLN induced to the sensor around the moving object, to detect one's hand movement and extract gesture frames from the detected signals. Signals from the EPS sensors include a large amount of power line noise usually existing in the places such as rooms or buildings. Using the fact that the PLN is shielded in part by human access to the sensor, signals caused by motion or hand movement are detected. PLN consists mainly of signals with frequency of 60 Hz and its harmonics. In our proposed method, signals only 120 Hz component in frequency domain are chosen selectively and exclusively utilized for detection of hand movement. We use FFT to measure a spectral-separated frequency signal. The signals obtained from sensors in this way are continued to be compared with the threshold preset in advance. Once motion signals are detected passing throng the threshold, we determine the motion frame based on period between the first threshold passing time and the last one. The motion detection rate of our proposed method was about 90% while the correct frame extraction rate was about 85%. The method like our method, which use PLN signal in order to extract useful data about motion movement from non-contact mode EPS sensors, has been rarely reported or published in recent. This research results can be expected to be useful especially in circumstance of having surrounding PLN.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.53-61
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• 2012

This paper proposes a real-time distance measurement system of high temperature and high speed target using infrared stereo camera. We construct an infrared stereo camera system that measure the difference between target and background temperatures for automatic target measurement. First, the proposed method detects target region based on target motion and intensity variation of local region using difference between target and background temperatures. Second, stereo matching by left and right target information is used to estimate disparity about real-time distance of target. In the proposed method using infrared stereo camera system, we compare distances in three dimension trajectory measuring instrument and in infrared stereo camera measurement. In this experiment from three video data, the result shows an average 9.68% distance error rate. The proposed method is suitable for distance and position measurement of varied targets using infrared stereo system.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.105-114
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• 2011

The roadmap-based planning is a path planning method which is used widely for a goal-directed movement in Robotics and has been applied to the world of computer animation such as computer games. However it is unnatural for computer characters to follow the path planned by the roadmap method as it is performed in Robotics. Flocking which is used for realistic and natural movements in computer animation enables character's movement by using a few simple rules without planning unlike the roadmap method. However it is impossible to achieve a goal-directed movement with flocking only because it does not keep states. In this paper we propose a simulation method which combines planning based on the road map with reactive actions for natural movements along the path planned. We define and implement steering behaviors for a leader which are needed to follow the trajectory naturally by analysing characteristics of roadmap-based paths and for the rest of members which follow the leader in various manners by detecting obstacles. The simulations are performed and demonstrated by using the implemented steering behaviors on every possible combination of roadmap-based path planning methods and models of configuration spaces. We also show that the detection of obstacle-collisions can be done effectively because paths are planned in the configuration space in which a moving object is reduced to a point.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.56-68
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• 2022

In this paper, we propose a compression method for multi-resolution feature maps for VCM. The proposed compression method removes the redundancy between the channels and resolution levels of the multi-resolution feature map through PCA-based transformation. According to each characteristic, the basis vectors and mean vector used for transformation, and the transformation coefficient obtained through the transformation are compressed using a VVC-based coder and DeepCABAC. In order to evaluate performance of the proposed method, the object detection performance was measured for the OpenImageV6 and COCO 2017 validation set, and the BD-rate of MPEG-VCM anchor and feature map compression anchor proposed in this paper was compared using bpp and mAP. As a result of the experiment, the proposed method shows a 25.71% BD-rate performance improvement compared to feature map compression anchor in OpenImageV6. Furthermore, for large objects of the COCO 2017 validation set, the BD-rate performance is improved by up to 43.72% compared to the MPEG-VCM anchor.