• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.270-274
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• 2015

We suggest that HSV Color Space may be used to detect a vehicle detecting system at nighttime. It is essential that a licence plate should be extracted when a vehicle is under surveillance. To do so, a licence plate may be enlarged to certain size after the aimed vehicle is taken picture from a distance by using Pan-Tilt-Zoom Camera. Either Mean-Shift or Optical Flow Algorithm is generally used for the purpose of a vehicle detection and trace, even though those algorithms have tendency to have difficulty in detection and trace a vehicle at night. By utilizing the fact that a headlight or taillight of a vehicle stands out when an input image is converted in to HSV Color Space, we are able to achieve improvement on those algorithms for the vehicle detection and trace. In this paper, we have shown that at night, the suggested method is efficient enough to detect a vehicle 93.9% from the front and 97.7% from the back.

• Journal of Digital Contents Society
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• v.3 no.1
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• pp.1-9
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• 2002

This paper is proposed to algorithm for measuring traffic information automatically, for example, volume count, speed and occupancy rate, from CCTV camera images installed on highway, add to function of image detectors which can be collected the traffic information. Recently the method of traffic informations are counted in lane one by one, but this manner is occurred critical errors by occlusion frequently in case of passing larger vehicles(bus, truck etc.) and is impossible to measure in the 8 lanes of highway. In this paper, installed the detection area include with all lanes, traffic informations are collected using tracking algorithm with passing vehicles individually in this detection area, thus possible to detect all of 8 lanes. The experiment have been conducted two different real road scenes for 20 minutes. For the experiments, the images are provided with CCTV camera which was installed at Kiheung Interchange upstream of Kyongbu highway, and video recording images at Chungkye Tunnel. For image processing, images captured by frame-grabber board 30 frames per second, $640{\times}480$ pixels resolution and 256 gray-levels to reduce the total amount of data to be interpreted.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.728-737
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• 2015

Stitching algorithm obtain a descriptor of the feature points extracted from multiple images, and create a single image through the matching process between the each of the feature points. In this paper, a feature extraction and matching techniques for the creation of a high-speed panorama using video input is proposed. Features from Accelerated Segment Test(FAST) is used for the feature extraction at high speed. A new feature point matching process, different from the conventional method is proposed. In the matching process, by tracking region containing the feature point through the Mean shift vector required for matching is obtained. Obtained vector is used to match the extracted feature points. In order to remove the outlier, the RANdom Sample Consensus(RANSAC) method is used. By obtaining a homography transformation matrix of the two input images, a single panoramic image is generated. Through experimental results, we show that the proposed algorithm improve of speed panoramic image generation compared to than the existing method.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.67-74
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• 2012

In this paper, we propose an efficient dynamic background modelling method by using eigenbackground to extract moving objects from video stream. Even if a background model has been created, the model has to be updated to adapt to change due to several reasons such as weather or lighting. In this paper, we update a background model based on R-SVD method. At this time we define a change ratio of images and update the model dynamically according this value. Also eigenbackground need to be modelled by using sufficient training images for accurate models but we reorganize input images to reduce the number of images for training models. Through simulation, we show that the proposed method improves the performance against traditional eigenbackground method without background updating and a previous method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.155-164
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• 2020

This study measured the effect of PPL(Product Placement: PPL) in OTT(Over The Top) to search a new advertising revenue model according to the change of viewers' video content consumption patterns. On the first, by two research steps, the experiment was carried out using an eye-tracker and then a survey as the second step was administered asking subjects about their attitude about advertising messages, attitude about brand, and intention to purchase the brands used in the experiments. Specifically, the PPL materials used in the experiments were classified with three parts. This study has the meaning as approaching to the PPL research with new methodology by quantitatively access through the eye tracking of the subjects beyond the conventional qualitative measure that depends only on the memory of them. This research aims to find the possibility of indirect advertising as a new revenue model in the OTT environment.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.20-28
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• 2012

Gait analysis is an examination which extracts objective information from observing human gait and assesses the function. The equipments used recently for gait analysis are expensive due to multiple cameras and force plates, and require the large space to set up the system. In this paper, we proposed a method to measure human gait motions in 3D from a monocular video. Our approach was based on particle filtering to track human motion without training data and previous information about a gait. We used dynamics to make physics-based motions with the consideration of contacts between feet and base. In a walking sequence, our approach showed the mean angular error of $12.4^{\circ}$ over all joints, which was much smaller than the error of $34.6^{\circ}$ with the conventional particle filter. These results showed that a monocular camera is able to replace the existing complicated system for measuring human gait quantitatively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.57-64
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• 2009

This paper presents the hardware implementation of the pyramidal KLT(Kanade-Lucas-Tomasi) feature tracker. Because of its high computational complexity, it is not easy to implement a real-time KLT feature tracker using general-purpose processors. A hardware implementation of the pyramidal KLT feature tracker using FPGA(Field Programmable Gate Array) is described in this paper with emphasis on 1) adaptive adjustment of threshold in feature extraction under diverse lighting conditions, and 2) modification of the tracking algorithm to accomodate parallel processing and to overcome memory constraints such as capacity and bandwidth limitation. The effectiveness of the implementation was evaluated over ones produced by its software implementation. The throughput of the FPGA-based tracker was 30 frames/sec for video images with size of $720{\times}480$.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.1-8
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• 2016

In the recently, violent crime and accidental crime has been generated continuously. Consequently, people anxiety has been heightened. The Closed Circuit Television (CCTV) has been used to ensure the security and evidence for the crimes. However, the video captured from CCTV has being used in the post-processing to apply to the evidence. In this paper, we propose a flexible multi-level models for estimating whether dangerous behavior and the environment and context for pedestrians. The situation analysis builds the knowledge for the pedestrians tracking. Finally, the decision step decides and notifies the threat situation when the behavior observed object is determined to abnormal behavior. Thereby, tracking the behavior of objects in a multi-region, it can be seen that the risk of the object behavior. It can be predicted by the behavior prediction of crime.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.123-128
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• 2012

In this paper, we propose a landmark-detection system of object for more accurate object recognition. The landmark-detection system of object becomes divided into a learning stage and a detection stage. A learning stage is created an interest-region model to set up a search region of each landmark as pre-information necessary for a detection stage and is created a detector by each landmark to detect a landmark in a search region. A detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. The proposed system uses Fast Fourier Transform to detect landmark, because the landmark-detection is fast. In addition, the system fails to track objects less likely. After we developed the proposed method was applied to environment video. As a result, the system that you want to track objects moving at an irregular rate, even if it was found that stable tracking. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.1-9
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• 2010

Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.