• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.355-361
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• 2006

In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.4
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• pp.55-63
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• 2007

The Group Digital Surveillance System for Fishery Safety and Security (GDSS-F2S) is to provide the target tracking information and the target identification information in order to secure an huge aquaculture farm-field from a thief. The two information, however, is not enough to indict the thief due to the lack of lawful evidences for the crime actions. To overcome this problem, we consider the target image information as one of solutions after discussion with the effective countermeasure tools for the crime actions with scenario-based analysis according to the geological feature of aquaculture farm-field. To capture the real-time image for the trespassing targets in the aquaculture farm-field area, we developed the image capture system which is consists of ultra sensitive CCD(Charge-Coupled Device) camera with 0.0001 Lux and supplementary devices. As results from the field tests for GDSS-F2S with image capture system, the high definite images of the vehicle number plate and shape, person's actions and features are obtainable not only day time but also very dark night without moon light. Thus it is cleary known that the improved GDSS-F2S with image capture system can provide much enough lawful evidences for the crime actions of targets.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6089-6097
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• 2012

This study suggested a method of detecting an incident inside tunnel by using camera that is installed within the tunnel. As for the proposed incident detection method, a static object, travel except vehicles, smoke, and contra-flow were detected by extracting the moving object through using the real-time background image differencing after receiving image from the camera, which is installed inside the tunnel. To detect the moving object within the tunnel, the positive background image was created by using the moving information of the object. The incident detection method was developed, which is strong in a change of lighting that occurs within the tunnel, and in influence of the external lighting that occurs in the entrance and exit of the tunnel. To examine the efficiency of the suggested method, the experimental images were acquired from Marae tunnel and Expo tunnel in Yeosu of Jeonnam and from Unam tunnel in Imsil of Jeonbuk. Number of images, which were used in experiment, included 20 cases for static object, 20 cases for travel except vehicles, 4 cases for smoke, and 10 cases for contra-flow. As for the detection rate, all of the static object, the travel except vehicles, and the contra-flow were detected in the experimental image. In case of smoke, 3 cases were detected. Thus, excellent performance could be confirmed. The proposed method is now under operation in Marae tunnel and Expo tunnel in Yeosu of Jeonnam and in Unam tunnel in Imsil of Jeonbuk. To examine accurate efficiency, the evaluation of performance is considered to be likely to be needed after acquiring the incident videos, which actually occur within tunnel.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.159-166
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• 2016

In this paper, an active object tracking system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-embedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18% on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• Aerospace Engineering and Technology
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• v.4 no.2
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• pp.107-116
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• 2005

As a unique payload of Komsat-2, MSC, comprising EOS(Electro-Optical Sub-system), PMU(Payload Management Unit) and PDTS(Payload Data Transmission Sub-system), is supposed to take pictures of one panchromatic and 4 multi-spectral image between wavelength 450mm~900mm, and is being under final Satellite I&T. It will perform the earth remote sensing with applications such as acquisition of high resolution images, surveillance of large scale disasters and its countermeasure, survey of natural resources, etc.. Under the hostile influence of the extreme space environmental conditions due to deep space and direct solar flux, the thermal design is especially of major importance in designing a payload. There are tight temperature range restrictions for electro-optical elements while on the other hand there are low power consumption requirements due to the limited energy source on the spacecraft. This paper describes details of thermal control system for MSC.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.149-161
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• 2005

Catadioptric mirrors are widely used in automatic surveillance system. The major drawback of catadioptric mirror is its unequal image resolution. Equidistance catadioptric mirror can be the solution to this problem. Even double panoramic structure can generate stereo images with single camera system. So two images obtained from double panoramic equidistance catadioptric mirror can be used in finding the depth and height values of object's points. But compared to the single catadioptric mirror. the image size of double panoramic system is relatively small. This leads to the severe accuracy problem in estimation. The exact axial alignment and the exact mount of mirror are the sources that can be avoided but the focal length variation is inevitable. In this paper, the effects of focal length variation on the computation of depth and height of object' point are explained and the effective focal length finding algorithm, using the assumption that the object's viewing angles are almost same in stereo images, is presented.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.95-101
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• 2006

A face detection plays an important role in face recognition, video surveillance, and human computer interaction. In this paper, we propose a progressive threshold method to detect human faces in real time. The consecutive face images are acquired from camera and transformed into YCbCr color space images. The skin color of the input images are separated using a skin color filter in the YCbCr color space and some candidated face areas are decided by connected component analysis. The intensity equalization is performed to avoid the effect of many circumstances and an arbitrary threshold value is applied to get binary images. The eye area can be detected because the area is clearly distinguished from others in the binary image progressive threshold method searches for an optimal eye area by progressively increasing threshold from low values. After progressive thresholding, the eye area is normalized and verified by back propagation algorithm to finalize the face detection.

• Korean Institute of Interior Design Journal
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• v.22 no.6
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• pp.40-48
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• 2013

Utilization of CCTV in crime prevention for public safety is accepted as the most effective measure in terms of crime prevention and control. Also, it is frequently used as a device that shows evidence of an unexpected situation or record on public social relationship. However, it is rare to find a study that qualitatively accessed the monitoring performance of a certain space depending on the choice and positioning of CCTVs. Thus, this study suggested a technology that can quantitatively compare and assess the monitoring performance of CCTVs depending on view angle and effective sight range of cameras as well as the monitoring performance depending on positioning measures. For the analysis, the concept of 3-dimensional surveillance field in the form of a frustum was suggested while deriving 3-dimensional range of sight and quantitative monitoring performance by applying Isovist theory. For the analysis technology, space of analysis subject, point of view (camera), and target point (measurement node) were installed at a 3-dimensional space and in use of ray-tracing algorithm, the line segment that was visually connected between the point of view and target point was extracted and accumulated. For such verification, analysis application was constructed and then applied to four alternative models on view angle and distance as well as four alternatives on positioning in order to verify its efficacy. Through the experiment, it was possible to compare and assess visibility depending on alternatives while quantifying the results by understanding the shadow areas beyond the monitoring range.