• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.178-181
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• 2011

With the development of mobile devices and intelligent surveillance system loaded with pan/tilt cameras, object tracking with non-stationary cameras has become a topic with increasing importancy. Since it is difficult to model a background image in a non-stationary camera environment, colors and texture are the most important features in the tracking algorithm. However, colors in the background similar to those in the target arise instability in the tracking. Recently, we proposed a robust color based tracking algorithm that uses an area weighted centroid shift. In this letter, we update the model such that it becomes more stable against background colors. The proposed algorithm also incorporates time filtering by adding an additional energy term to the energy functional.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.495-502
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• 2003

This paper focuses on the implementation of an efficient tracking method of a moving object using optimal representative blocks by way of a pan-tilt camera. The key idea is derived from the fact that when the image size of a moving object is shrunk in an image frame according to the distance between the mobile robot camera and the object in motion, the tracking performance of a moving object can be improved by reducing the size of representative blocks according to the object image size. Motion estimations using Edge Detection (ED) and Block-Matching Algorithm (BMA) are regularly employed to track objects by vision sensors. However, these methods often neglect the real-time vision data since these schemes suffer from heavy computational load. In this paper, a representative block able to significantly reduce the amount of data to be computed, is defined and optimized by changing the size of representative blocks according to the size of the object in the image frame in order to improve tracking performance. The proposed algorithm is verified experimentally by using a two degree-of- freedom active camera mounted on a mobile robot.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.136-141
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• 2009

This paper proposed a framework for handover method in continuously tracking a person of interest across cooperative pan-tilt-zoom (PTZ) cameras. The algorithm here is based on a robust non-parametric technique for climbing density gradients to find the peak of probability distributions called the mean shift algorithm. Most tracking algorithms use only one cue (such as color). The color features are not always discriminative enough for target localization because illumination or viewpoints tend to change. Moreover the background may be of a color similar to that of the target. In our proposed system, the continuous person tracking across cooperative PTZ cameras by mean shift tracking that using color and shape histogram to be feature distributions. Color and shape distributions of interested person are used to register the target person across cameras. For the first camera, we select interested person for tracking using skin color, cloth color and boundary of body. To handover tracking process between two cameras, the second camera receives color and shape cues of a target person from the first camera and using linear color calibration to help with handover process. Our experimental results demonstrate color and shape feature in mean shift algorithm is capable for continuously and accurately track the target person across cameras.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.55-60
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• 2012

When operating a surveillance system in the maritime environment, its stabilization performance is degraded due to undesirable disturbance motions. For accurate target pointing of a 2-axes surveillance system on shipboard, the kinematic stabilization is first applied, which compensates a deviated motion via coordinate transformations of attitude information. Resultantly, the stabilization error is no longer reduced due to less accuracy of a MEMS sensor and kinematic constraint, leading to introduction of the image stabilization as a complementary function. And for real-time execution of the present dual stabilization scheme, a HILS (Hardware In the Loop Simulation) test bed including 6-dof motion simulator has been constructed, and through the obtained HILS data, it has been confirmed that the stabilization is successfully.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose the algorithm for making panoramic background and object tacking using pan-tilt-zoom camera. We draw an analogy relation between images for cylinder projection, rearrange of images, stitching, and blending. We can then make the panoramic background, and can track the object use the panoramic background. After generated the background, the proposed algorithm tracks the moving object. Therefore it can detect the wide area, and it tracks the object continuously. So the proposed algorithm is able to use at wide area to detect and track the object.

• Journal of IKEEE
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• v.17 no.2
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• pp.104-110
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• 2013

In this paper, we introduce a smart care surveillance system which can support various CCTV cameras. In order to monitor an emergency requester in case of emergency, the server performs automatical CCTV Pan, Tilt, and Zoom control based on the location coordinates of the emergency requester. Also, a server finds and tracks the emergency requester using image processing and the updated location information. We implement a smart care surveillance system using the Genetec SDK tool to support various CCTV cameras. The efficiency of the rescue operation with the smart care surveillance system can be improved because rescuer can quickly control and monitor the requester's CCTV images.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.743-748
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• 2011

In this paper, we propose a collaborative tracking algorithm for intelligent video surveillance systems using the multiple network cameras. To do this, each camera detects a moving object and it's movement direction by motion templates. Once a moving object is detect, the Kalman filter is used to reduce noises, and a collaborative tracking camera is selected according to the movement direction and the camera state. In this procedure, Pan-Tilt-Zoom(PTZ) parameters are assigned to obtain clear images. Finally, some experiments show the validity of the proposed method.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.151-162
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• 2004

Current methods for construction site modeling employ large, expensive laser range scanners that produce dense range point clouds of a scene from different perspectives. Days of skilled interpretation and of automatic segmentation may be required to convert the clouds to a finished CAD model. The dynamic nature of the construction environment requires that a real-time local area modeling system be capable of handling a rapidly changing and uncertain work environment. However, in practice, large, simple, and reasonably accurate embodying volumes are adequate feedback to an operator who, for instance, is attempting to place materials in the midst of obstacles with an occluded view. For real-time obstacle avoidance and automated equipment control functions, such volumes also facilitate computational tractability. In this research, a human operator's ability to quickly evaluate and associate objects in a scene is exploited. The operator directs a laser range finder mounted on a pan and tilt unit to collect range points on objects throughout the workspace. These groups of points form sparse range point clouds. These sparse clouds are then used to create geometric primitives for visualization and modeling purposes. Experimental results indicate that these models can be created rapidly and with sufficient accuracy for automated obstacle avoidance and equipment control functions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.2
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• pp.65-70
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• 2008

Smart surveillance, is the use of automatic video analysis technologies in video surveillance applications. We present a robust object tracking method using pan-tilt-zoom camera for intelligent surveillance System, As the result of the experiment using 78 vehicle, the success rate of the tracking for moving object & non-moving object werw 97.4% and 91%. and 84.6%. the success rate o PTZ control for license plate image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.694-701
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• 2004

In this paper, we proposed a feature-based tracking system that traces moving objects with a pan-tilt camera after separating the global motion of an active camera and the local motion of moving objects. The tracking system traces only the local motion of the comer features in the foreground objects by finding the block motions between two consecutive frames using a block-based motion estimation and eliminating the global motion from the block motions. For the robust estimation of the camera motion using only the background motion, we suggest a dominant motion extraction to classify the background motions from the block motions. We also propose an efficient clustering algorithm based on the attributes of motion trajectories of corner features to remove the motions of noise objects from the separated local motion. The proposed tracking system has demonstrated good performance for several test video sequences.