• Journal of Broadcast Engineering
• /
• v.24 no.5
• /
• pp.802-812
• /
• 2019

With the rapid development in the field of unmanned aerial vehicles(UAVs) and drones, higher request to development of a surveillance system for a drone is putting forward. Since surveillance systems with fixed cameras have a limited range, a development of surveillance systems with a moving camera applicable to PTZ(Pan-Tilt-Zoom) cameras is required. Selecting the features for object plays a critical role in tracking, and the object has to be represented by their shapes or appearances. Considering these conditions, in this paper, an object tracking method with optical flow is introduced to track a tiny drone with a moving camera. In addition, a tracking method combined with kalman filter is proposed to track continuously even when tracking is failed. Experiments are tested on sequences which have a target from the minimal 12 pixels to the maximal 56337 pixels, the proposed method achieves average precision of 175% improvement. Also, experimental results show the proposed method tracks a target which has a size of 12pixels.

• Proceedings of the KIEE Conference
• /
• 2001.11c
• /
• pp.365-368
• /
• 2001

This work describes a real-time method, based on motion energy detection, for detecting and tracking moving object in the consecutive image sequences. The motion of moving objects is detected by taking the difference of the two consecutive image frames. In addition an edge information of the current image is utilized in order to further increase the accuracy of detection. We can track the moving objects continuously by detecting the motion of objects from the sequence of image frames. A prototype system has been implemented using a TI TMS320C6201 EVM fixed-point DSP board, which can successfully track a moving human in real-time.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.99.4-99
• /
• 2002

A two-dimensional moving target is necessarily captured by a 5 dot robot system using a robot vision technique. Here, a robot vision system with a visual skill so that it can take information for a moving target or object, specially two dimensionally moving, is introduced and its algorithm and control strategy are presented associated with it. The tracking algorithm is proposed and its performance is verified by experiment. The camera first captures the object, then it captures again after certain second. The position difference generates the horizontal and vertical velocities of the moving target, hence the final destination is estimated at gripping line. At the same time, the robot s...

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.4
• /
• pp.578-585
• /
• 2018

In this paper, we propose a classification and theft detection system for human and livestock for various moving objects in a barn. To do this, first, we extract the moving objects using the GMM method. Second, the noise generated when extracting the moving object is removed, and the moving object is recognized through the labeling method. And we propose a method to classify human and livestock using model formation and color for the unique form of the detected moving object. In addition, we propose a method of tracking and overlapping the classified moving objects using Kalman filter. Through this overlap determination method, an event notifying a dangerous situation is generated and a theft determination system is constructed. Finally, we demonstrate the feasibility and applicability of the proposed system through several experiments.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.8
• /
• pp.41-53
• /
• 1993

The tasks which detect and track moving objects, by analyzing dynamic images taken at a constant time interval, are essential in various applications. This paper suggests how to utilize domain-specific knowledge and motional knowledge for detecting and tracking moving objects. That is, The trajectory information of a moving object is to be used for generating hypotheses on expected motion and expected position of moving objects, and the domain-specific knowledge is to be used for verifying the generated hypotheses.

• Proceedings of the IEEK Conference
• /
• 2004.08c
• /
• pp.823-826
• /
• 2004

In this paper, A tracking of the moving objects using normalized hue distribution in HSI color model was proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area. Hue information of the detected moving area are normalized by 24 levels from $0^{\circ}$ to $3600^{\circ}A$ distance in between normalized levels with a hue distribution chart of the normalized moving objects is used for the identity distinction feature parameters of the moving objects. To examine proposed method in this paper, image of moving cars are obtained by setting up three cameras at different places every 1 km on outer motorway. The simulation results of identity distinction show that it is possible to distinct the identity a distance in between normalization levels of a hue distribution chart without background.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
• /
• v.11 no.1
• /
• pp.1-9
• /
• 2012

In this paper, we proposed a method of improving the location estimation error existing in RTLS (Real Time Location Service) system for the individual mobility. As ubiquitous age comes, interest for indoor location tracking system is getting more increased. However, existing indoor location tracking system does not correspond actively to frequent changes in indoor environment, and there is a problem that correct location measurement of moving object is difficult due to NLOS (non-line-of-sight) property of indoor environment. Purpose of this paper is to propose an environment accommodation location tracking system that improves the location precision of moving object and grasps location of the object effectively, which is essential an element effectively to provide service and satisfy various users' request.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2005.11a
• /
• pp.113-117
• /
• 2005

This paper describes a visual control scheme, fuzzy logic system for visual servoing of an autonomous mobile robot. An existing communication autonomous mobile robot always needs to keep the object in image to detect the moving object. This is a problem in an autonomous mobile robot for spontaneous activity. To solve it, some features for an object are taken from an image and then use in the design of fuzzy logic system for decision of moving location and direction of visual servoing contrivance(apparatus). So continuous tracking is possible by moving the visual servoing contrivance. We present some simulation results and further studies in the Section of Simulation and Concluding Remarks.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.839-840
• /
• 2006

Our paper proposes a novel moving object tracking scheme for biped robot using a single camera. For walking control of a biped robot we analyze the dynamics of a three-dimensional inverted pendulum model. This analysis leads us a simple linear dynamics. And, the control parameter of the biped robot is derived from the feedback signal which converges the position of a image feature to the feature position of a desired image and the feedforward signal which compensates the motion component due to the moving object.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.2
• /
• pp.344-352
• /
• 2003

An effective algorithm for implementation of which detects moving object from image sequences. predicts the direction of it. and drives the camera in real time is proposed. In static camera, for robust motion detection from a dynamic background scene, the proposed algorithm performs statistical modeling of moving objects and background, and trains the statistical modeling of moving objects and background, and trains the statistical feature of background with the initial parts of sequence which have no moving objects. Active camera moving objects are segmented by following procedure, an improved order adaptive lattice structured linear predictor is used. The proposed algorithm shows robust object tracking results in the environment of static or active camera. It can be used for the unmanned surveillance system, traffic monitoring system, and autonomous vehicle.