• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.619-628
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• 2013

In this paper, we describe a strongly improved tracking method using combination of CAMshift and Kalman filter algorithm. CAMshift algorithm doesn't consider the object's moving direction and velocity information when it set the search windows for tracking. However if Kalman filter is combined with CAMshift for setting the search window, it can accurately predict the object's location with the object's present location and velocity information. By using this prediction before CAMshift algorithm, we can track fast moving objects successfully. Also in this research, we show better tracking results than conventional approaches which make use of single color information by using both color information of HSV and YCrCb simultaneously. This modified approach obtains more robust color segmentation than others using single color information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4160-4173
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• 2019

Borescopes facilitate the inspection of areas inside machines and systems that are not directly accessible for visual inspection. They offer real-time, up-close access to confined and hard-to-access spaces without having to dismantle or destructure the object under inspection. Borescopes are ideal instruments for routine maintenance, quality inspection and monitoring of systems and structures. The main application being fault or defect detection, it is useful to have measuring capability to quantify object dimensions in a target area. High-end borescopes use multi-optic solutions to provide measurement information of viewed objects. Multi-optic solutions can provide accurate measurements at the expense of structural complexity and cost increase. Measuring functionality is often unavailable in low-end, single camera borescopes. In this paper, a single camera measurement solution that enables the size estimation of viewed objects is proposed. The proposed solution computes and overlays a scaled grid of known spacing value over the screen view, enabling the human inspector to estimate the size of the objects in view. The proposed method provides a simple means of measurement that is applicable to low-end borescopes with no built-in measurement capability.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.5
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• pp.195-204
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• 2018

In this paper, we propose both a new loss function and an online hard example mining scheme for improving the performance of single-stage object detectors which use deep convolutional neural networks. The proposed loss function and the online hard example mining scheme can not only overcome the problem of imbalance between the number of annotated objects and the number of background examples, but also improve the localization accuracy of each object. Therefore, the loss function and the mining scheme can provide intrinsically fast single-stage detectors with detection performance higher than or similar to that of two-stage detectors. In experiments conducted with the PASCAL VOC 2007 benchmark dataset, we show that the proposed loss function and the online hard example mining scheme can improve the performance of single-stage object detectors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2669-2688
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• 2016

An efficient and effective unsupervised single moving object detection framework is presented in this paper. Given the sparsely labelled trajectory points, we adopt a coarse-to-fine strategy to detect and segment the foreground from the background. The superpixel level coarse segmentation reduces the complexity of subsequent processing, and the pixel level refinement improves the segmentation accuracy. A distance measurement is devised in the coarse segmentation stage to measure the similarities between generated superpixels, which can then be used for clustering. Moreover, a Quadmap is introduced to facilitate the refinement in the fine segmentation stage. According to the experiments, our algorithm is effective and efficient, and favorable results can be achieved compared with state-of-the-art methods.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2359-2364
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• 2017

This paper proposes a scale factor based range estimation method using a sum of squares (SOS) method. Many previous studies measured distance by using a camera, which usually required two cameras and a long computation time for image processing. To overcome these disadvantages, we propose a range estimation method for an object using a single moving camera. A SOS-based Luenberger observer is proposed to estimate the range on the basis of the Euclidean geometry of the object. By using a scale factor, the proposed method can realize a faster operation speed compared with the previous methods. The validity of the proposed method is verified through simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.153.2-153
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• 2001

A technique is described for producing a virtual object with realistic motion. A 3-D human motion model is obtained by applying a developed motion capturing technique to a real human in motion. Factorization method is a technique for recovering 3-D shape of a rigid object from a single video image stream without using camera parameters. The technique is extended for recovering 3-D human motions. The proposed system is composed of three fixed cameras which take video images of a human motion. Three obtained image sequences are analyzed to yield measurement matrices at individual sampling times, and they are merged into a single measurement matrix to which the factorization is applied and the 3-D human motion is recovered ...

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.187-192
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• 1999

Noncontact measuring methodology of 3-dimensional profile using CCD camera are very attractive because of it's high measuring speed and its's high sensitivity. Especially when projecting a grid pattern over the object, the captured image have 3 dimensional information of the object. Projection moire extract 3-D information with another grid pattern in front of CCD camera. However phase measuring profilometry(PMP) obtain similar results without additional grid pattern. In this paper, the projection moire are compared with the PMP mathematically, and it is shown that PMP can generate moire image with simple mathematical computations. Experimental works are also carried out showing the same results. It is shown that using a single gird pattern, moire image can be obtained directly without any mathematical operation when some conditions are satisfied.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.167-175
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• 2022

With the recent expansion of electric kickboards and bicycle sharing services, more and more people use them. In addition, the rapid growth of the delivery business due to the COVID-19 has significantly increased the use of two-wheeled vehicles and personal mobility. As the accident rate increases, the rule related to the two-wheeled vehicles is changed to 'mandatory helmets for kickboards and single-person transportation' and was revised to prevent boarding itself without driver's license. In this paper, we propose a wearable smart safety equipment, called SafetyHelmet, that can keep helmet-wearing duty and lower the accident rate with the communication between helmets and mobile devices. To make this function available, we propose a safe driving assistance function by notifying the driver when an object that interferes with driving such as persons or other vehicles are detected by applying the YOLO v5 object detection algorithm. Therefore it is intended to provide a safer driving assistance by reducing the failure rate to identify dangers while driving single-person transportation.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.556-565
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• 2014

This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.153-161
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• 2019

Discrimination of media object segments in wireless home proxies has a significant impact on caching delay, and caching delay degrades the performance of the proxy. In this paper, we propose a Single Fetching Smart Caching (SFSC) strategy and a Multi-Fetching Smart Caching (MFSC) strategy to improve the proxy performance of the home network and improve the caching performance for media object segments. The SFSC strategy is a technique that performs caching by sequential fetching of object segments requested by the home node one at a time, which guarantees a faster cache hit rate, and the MFSC strategy is a technique that caches the media object segments by blocking object segments requested by the home node one at a time, which improves the throughput of cache. Simulation results show that the cache hit rate and the caching delay are more efficient than the MFSC technique, and the throughput of the object segment is more efficient than that of the SFSC technique.