• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.111-116
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• 2019

The fire detectors used in the engine rooms of ships offer only a slow response to emergencies because smoke or heat must reach detectors installed on ceilings, but the air flow in engine rooms can be very fluid depending on the use of equipment. In order to overcome these disadvantages, much research on video-based fire detection has been conducted in recent years. Video-based fire detection is effective for initial detection of fire because it is not affected by air flow and transmission speed is fast. In this paper, experiments were performed using images of smoke from a smoke generator in an engine room. Data generated using LBP and GLCM operators that extract the textural features of smoke was classified using SVM, which is a machine learning classifier. Even if smoke did not rise to the ceiling, where detectors were installed, smoke detection was confirmed using the image-based technique.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.154-162
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• 2012

Facial expression and gesture of the actors can be magnified or understated depending on the size of the camera framing. The direction, quality, and quantity of the lighting can also make the actors look different. That's why we have to deliberate how to photograph the actors who will be projected on the screen. This thesis shows the way of improving performance and emphasizing each character with camera and lighting. You will also find out how visual elements influence the actors and their performances.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.57-65
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• 2010

In this paper, we propose a new real-time algorithm detecting the flame and smoke in digital CCTV images. Because the forest fire causes the enormous human life and damage of property, the early management according to the early sensing is very important. The proposed algorithm for monitoring forest fire is classified into the flame sensing and detection of smoke. The flame sensing algorithm detects a flame through the conditional test at YCbCr color model from the single frame. For the detection of smoke, firstly the background range is set by using differences between current picture and the average picture among the adjacent frames in the weighted value, and the pixels which get out of this range and have a gray-scale are detected in the smoke area. Because the proposed flame sensing algorithm is stronger than the existing algorithms in the change of the illuminance according to the quantity of sunshine, and the smoke detection algorithm senses the pixel of a gray-scale with the smoke considering the amount of change for unit time, the effective early forest fire detection is possible. The experimental results indicate that the proposed algorithm provides better performance than existing algorithms.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.1-6
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• 2014

Color image processing based on smoke detection is suitable detecting target to early detection of fire smoke. A method for detecting the smoke is processed in the pre-processing movement and color. And Next, characteristics of smoke such as diffusion, texture, shape, and directionality are used to post-processing. In this paper, propose the detection method of density distribution characteristic in characteristics of smoke. the generate a candidate regions by color thresholding image in Detecting the movement of smoke to the 10Frame interval and accumulated while 1second image. then check whether the pattern of the smoke by candidate regions to applying OBTP(Object Block Ternary Pattern). every processing is Block-based processing, moving detection is decided the candidate regions of the moving object by applying an adaptive threshold to frame difference image. The decided candidate region accumulates one second and apply the threshold condition of the smoke color. make the ternary pattern compare the center block value with block value of 16 position in each candidate region of the smoke, and determine the smoke by compare the candidate ternary pattern and smoke ternary pattern.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.149-154
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• 2014

Detection performance of fire detection in the outdoor depends on weather conditions, the shadow by the movement of the sun, or illumination changes. In this paper, a smoke detection in conjunction with a robust background estimate algorithm to environment change in the outdoor in daytime is proposed. Gaussian Mixture Model (GMM) is applied as background estimation, and also, statistical characteristics of smoke is applied to detect the smoke for separated candidate region. Through the experiments with input videos obtained from a various weather conditions, the proposed algorithms were useful to detect smoke in the outdoor.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.43-52
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• 2011

With the rapid development of technology, skyscrapers are widely spread and they are tightly coupled. If fire occurs in a building, it is easily spread to neighboring buildings, resulting in the large number of victims and property damages. To remove fire disasters, the need for early fire detection techniques is increasing. To detect fire, detecting devices for heat, smoke, and flame have been used widely. However, this paper surveys and presents the latest research which focuses on early smoke and flame detection algorithms and systems with camera's input images. In addition, this paper implements and evaluates the performance of these flame and smoke detection algorithms with several types of movies.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.155-160
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• 2014

In this paper, an algorithm using RGB-depth camera is proposed to detect smoke in interrior. RGB-depth camera, the Kinect provides RGB color image and depth information. The Kinect sensor consists of an infra-red laser emitter, infra-red camera and an RGB camera. A specific pattern of speckles radiated from the laser source is projected onto the scene. This pattern is captured by the infra-red camera and is analyzed to get depth information. The distance of each speckle of the specific pattern is measured and the depth of object is estimated. As the depth of object is highly changed, the depth of object plain can not be determined by the Kinect. The depth of smoke can not be determined too because the density of smoke is changed with constant frequency and intensity of infra-red image is varied between each pixels. In this paper, a smoke detection algorithm using characteristics of the Kinect is proposed. The region that the depth information is not determined sets the candidate region of smoke. If the intensity of the candidate region of color image is larger than a threshold, the region is confirmed as smoke region. As results of simulations, it is shown that the proposed method is effective to detect smoke in interior.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.12
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• pp.947-954
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• 2017

In case of a fire in urban large structures such as super high-rise buildings, evacuation guidance must be provided to the occupants in order to minimize human deaths and injuries. Therefore, it is essential to provide emergency evacuation guidance when a major fire occurs. In order to effectively support evacuation guidance, it is important to identify major items such as fire location, occupant position, escape route, etc. Also, it is important to quickly identify evacuation areas where residents can safely evacuate from a fire. In this paper, we analyze the CCTV video and propose a method of measuring visibility of the evacuation zone from the smoke caused by the fire in order to determine the safety of evacuation area. To do this, we first extract the background video from the smoke video to measure the visibility of the specific area due to smoke. After generating an edge-extracted image for the extracted background video, the degree of visibility is measured by calculating the change in the edge strength due to smoke.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.1007-1012
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• 2014

This study investigates the basic elements of film acting based on Lee Strasberg's emotional memory. Acting in Korean film and TV drama often meets difficult circumstances. Therefore, I strongly suggest Lee Strasberg' American Method to film actors and students. This method refers to affective memory that Lee Strasberg devised for film acting at the Actors Studio. Another main point of this method is to overcome difficulties created from the camera use and shooting process. It is evident practicing affective memory would help actors perform better in their field.

• Journal of Broadcast Engineering
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• v.1 no.1
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• pp.55-61
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• 1996

We propose an algorithm for video effects of sports broadcasting that informs TV viewers of a sports player's sequential performing forms and locus in detail when gymnastic game such as 'vault' is broadcasted. It records the image sequences while a player is performing, extracts only the player's performing forms from background scenes by a proposed algorithm, superposes them sequentially on a background scene, and broadcasts them with slow speed. This system named as 'Multi-Motion' has ever been used in NHK live broadcasting for 1995 World Gymnastics Championships held in Japan.