• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.62-70
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• 2012

In this paper, we propose the gunnery detection method based on reference frame modeling and frame difference method. The frame difference method is basic method in target detection, and it's applicable to the detection of moving targets. The goal of proposed method is the detection of gunnery target which has huge variation of energy and size in the time domain. So, proposed method is based on frame difference, and it guarantee real-time processing and high detection performance. In the method of frame difference, it's important to generate reference frame. In the proposed method, reference frame is modeled and updated in real time processing using statistical values for each pixels. We performed the simulation on 73 IR video data that has gunnery targets, and the experimental results showed that the proposed method has 95.7% detection ratio under condition that false alarm is 1 per hour.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.75.4-76
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• 2016

DEEP-South (Deep Ecliptic patrol of the Southern sky) is one of the secondary science projects of KMTNet (Korea Microlensing Telescope Network). The objective of this project is twofold, the physical characterization and the discovery of small Solar System bodies, focused on NEOs (Near Earth objects). In order to achieve the goals, we are implementing a software package to detect and report moving objects in the $18k{\times}18k$ mosaic CCD images of KMTNet. In this paper, we present preliminary results of the moving object detection experiments using the prototype MODP (Moving Object Detection Program). We utilize multiple images that are being taken at three KMTNet sites, towards the same target fields (TFs) obtained at different epochs. This prototype package employs existing softwares such as SExtractor (Source-Extracto) and SCAMP (Software for Calibrating Astrometry and Photometry); SExtractor generates catalogs, while SCAMP conducts precision astrometric calibration, then MODP determines if a point source is moving. We evaluated the astrometric accuracy and efficiency of the current version of MODP. The plan for upgrading MODP will also be mentioned.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.6
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• pp.321-328
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• 2018

This paper presents an automatic target tracking flight system using a PID controller based on velocity command of a multirotor UAV. The automatic flight system includes marker based onboard target detection and an automatic velocity command generation replacing manual controller. A quad-rotor UAV is equipped with a camera and an image processing computer to detect the marker in real time and to estimate the relative distance from the target. The marker tracking system consists of PID controller and generates velocity command based on the relative distance. The generated velocity command is used as the input of the UAV's original flight controller. The operation of the proposed system was verified through actual flight tests using a marker on top of a moving vehicle and tracks it to successfully demonstrate its capability using a quad-rotor UAV.

• Current Optics and Photonics
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• v.3 no.3
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• pp.204-209
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• 2019

In an optical interferometer that uses sinusoidal modulation and quadrature detection, the amplitude and offset of the interference signal vary with time, even without considering system noise. As a result, the circular Lissajous figure becomes elliptical, with wide lines. We propose and experimentally demonstrate a method for compensating quadrature detection error, based on digital signal processing to deal with scaling and fitting. In scaling, fluctuations in the amplitudes of in-phase and quadrature signals are compensated, and the scaled signals are fitted to a Lissajous unit circle. To do so, we scale the average fluctuation, remove the offset, and fit the ellipse to a unit circle. Our measurements of a target moving with uniform velocity show that we reduce quadrature detection error from 5 to 2 nanometers.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.90-96
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• 2017

Due to the merit of having wide range with low cost, HF radar's ship detection and tracking research as maritime surveillance system has been recently studied. Many ship detection and tracking algorithms have been developed so far, however, performance comparison cannot be conducted properly because the states of target ships (such as moving path, size, etc.) differ from each study. In this paper, we propose a simulator based on compact HF radar, which generates data according to the size and moving path of target ship. Given the generated data with identical ship state, it is possible to conduct performance comparison. In order to validate the proposed simulator, the simulated data has been compared with real data collected by the SeaSonde HF radar sites. As a result, it has been shown that our simulated data resembles the real data. Therefore, the performance of various detection or tracking algorithms can be compared and analyzed respectively by using our simulated data.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.1
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• pp.27-35
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• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.77-84
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• 2005

In most vision applications, we are frequently confronted with determining the position of object continuously. Generally, intertwined processes ire needed for target tracking, composed with tracking and control process. Each of these processes can be studied independently. In case of actual implementation we must consider the interaction between them to achieve robust performance. In this paper, the robust real time visual tracking in complex background is considered. A common approach to increase robustness of a tracking system is to use known geometric models (CAD model etc.) or to attach the marker. In case an object has arbitrary shape or it is difficult to attach the marker to object, we present a method to track the target easily as we set up the color and shape for a part of object previously. Robust detection can be achieved by integrating voting-based visual cues. Kalman filter is used to estimate the motion of moving object in 3D space, and this algorithm is tested in a pan/tilt robot system. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.1
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• pp.75-85
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• 1985

We have studied on the 2-D moving target tracking algorithm satisfying a real-time hardware implementation requirement. In this paper, a fast algorithm is developed based on the operator formulation and the variational algorithm f 10] . Here, we use the directed search for the maximum of the cross-correlation in order to obtain an initial estimate for the variational algorithm and decompose the scene into 16 smaller subblocks and apply the variational algorithm to each subblock sequentially with a new moving area detection method. We call the algorithm subblock based recursive algorithm. Compared with (10) , the ratio of the computational savings obtained from the proposed algorithm is 7 on the average.

• 전자공학회논문지 IE
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• v.47 no.2
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• pp.38-46
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• 2010

In this paper, an autonomous surveillance-tracking system for Workers monitoring basing on the stereo vision scheme is proposed. That is, analysing the characteristics of the cross-axis camera system through some experiments, a optimized stereo vision system is constructed and using this system an intelligent worker surveillance-tracking system is implemented, in which a target worker moving through the environments can be detected and tracked, and its resultant stereo location coordinates and moving trajectory in the world space also can be extracted. From some experiments on moving target surveillance-tracking, it is analyzed that the target's center location after being tracked is kept to be very low error ratio of 1.82%, 1.11% on average in the horizontal and vertical directions, respectively. And, the error ratio between the calculation and measurement values of the 3D location coordinates of the target person is found to be very low value of 2.5% for the test scenario on average. Accordingly, in this paper, a possibility of practical implementation of the intelligent stereo surveillance system for real-time tracking of a target worker moving through the environments and robust detection of the target's 3D location coordinates and moving trajectory in the real world is finally suggested.