• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.289-292
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• 2013

최근 많은 영상처리 연구자들 사이에서 마이크로소프트사의 실시간 깊이센서 '키넥트'가 상당한 관심을 받고 있다. '키넥트'는 실시간으로 깊이정보를 제공함과 동시에 별도의 센서를 부착하지 않고도 컴퓨터와의 인터렉션할 수 있는 가능성을 제공한다. 하지만 '키넥트'의 깊이영상은 홀 영역, 부정확한 경계, 낮은 해상도등의 많은 문제점을 지니고 있다. 이러한 부정확한 깊이 정보는 3차원 렌더링, 가상시점 영상 합성, 모션 인식 등에서 성능 저하를 야기한다. 따라서 본 논문에서는 깊이 정보 품질 향상기법에 관하여 깊이영상 신뢰도를 이용한 도메인 변환기반 해상도 상향 알고리듬을 제안한다. 정확하고 빠르게 홀 영역정보를 추정하기 위해 도메인 변환 기반의 경계 보존 필터링이 사용된다. 또한 다양한 깊이 영상의 노이즈를 효율적으로 제거하기 깊이 영상의 신뢰도를 이용한다. 실험결과를 통하여 제안하는 방법이 효율적으로 홀 영역을 채우고, 부정확한 경계를 제거하여 깊이 영상의 품질을 향상시키는 것을 확인할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.605-606
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• 2011

최근 PC 기반의 새로운 입력장치인 키넥트(Kinect) 센서에 대한 연구사 활발하게 진행되고 있다. 키넥트 센서의 가장 큰 이점은 2차원 평면 영상정보에 대하여 새롭게 추가된 깊이(Depth) 정보를 얻을 수 있다는 것이다. 이것은 이전에 등장했던 다른 인터페이스보다 새로운 차원의 인터페이스로서 2차원의 영상 정보로부터 한 차원 확장된 3차원의 정보를 활용할 수 있다는 점에서 그 의미가 크다고 볼 수 있다. 본 논문에서는 이러한 2차원 영상정보와 추가된 깊이 정보를 활용하여 사람의 영상정보와 사람의 위치 정보를 활용하여 위치한 환경의 조명을 제어할 수 있도록 시스템을 구성하였다. 또한, 키넥트의 다양한 성능을 검토하기위하여 3개의 키넥트를 사용하였으며 중첩된 영상정보를 30%의 중복도를 가지도록 구성하여 다양한 활용가능성을 검토하였다. 구현한 시스템을 통하여 사람을 추적할 수 있도록 알고리즘을 개발하고, 추적된 사람의 위치 정보를 통하여 LED 조명을 제어할 수 있는 키넥트 기반의 조명제어 시스템을 제시하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.40-42
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• 2019

색상 영상과 이에 상응하는 깊이 영상으로 3차원 비디오를 만드는 방법은 최근 키넥트 깊이 카메라와 같이 저가임에도 불구하고 높은 성능을 보이는 카메라가 시중에 출시되면서 다양한 형태의 응용분야에 많이 사용되기 시작했다[1]. 본 연구는 TOF(Time Of Flight) 카메라와 RGB 카메라가 같이 있는 키넥트를 이용해서 깊이 영상에서 보행자를 탐지한다. 전처리 작업으로 배경 깊이 맵을 미리 저장하고, 깊이의 차이로 보행자 유무를 알아낸다. 보행자를 지속적으로 탐지하기 위해 CAMShift 알고리즘을 사용해 라벨링과 보행자 추적을 하며, 보행자의 진행 방향과 속도를 탐지하기 위해 Dense Optical Flow를 사용해 보행자의 벡터 정보를 저장한다. 보행자가 깊이 맵 밖으로 나가면 해당 보행자에 대한 탐지를 종료한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.818-819
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• 2014

Recently there are many works conducted on utilizing the DIBR (Depth-Image-Based Rendering) based intermediate images for the three-dimensional displays that do not require the use of stereoscopic glasses. However the prior works have used expensive depth cameras to obtain high-resolution depth images since DIBR-based intermediate image generation method requires the accuracy for depth information. In this study, we have developed the simulation to generate multi-view intermediate images based on the depth and color images using Microsoft Kinect. This simulation aims to support the acquisition of multi-view intermediate images utilizing the low-resolution depth and color image from Kinect, and provides the integrated service for the quality evaluation of the intermediate images. This paper describes the architecture and the system implementation of this simulation program.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.279-282
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• 2017

Kinect depth sensor, a depth camera developed by Microsoft as a natural user interface for game appeared as a very useful tool in computer vision field. In this paper, due to kinect's depth sensor and its high frame rate, we developed a distance measurement system using Kinect camera to test it for unmanned vehicles which need vision systems to perceive the surrounding environment like human do in order to detect objects in their path. Therefore, kinect depth sensor is used to detect objects in its field of view and enhance the distance measurement system from objects to the vision sensor. Detected object is identified in accuracy way to determine if it is a real object or a pixel nose to reduce the processing time by ignoring pixels which are not a part of a real object. Using depth segmentation techniques along with Open CV library for image processing, we can identify present objects within Kinect camera's field of view and measure the distance from them to the sensor. Tests show promising results that this system can be used as well for autonomous vehicles equipped with low-cost range sensor, Kinect camera, for further processing depending on the application type when they reach a certain distance far from detected objects.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1183-1188
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• 2016

Kinect sensor version 2 is a kind of camera released by Microsoft as a computer vision and a natural user interface for game consoles like Xbox one. It allows acquiring color images, depth images, audio input and skeletal data with a high frame rate. In this paper, using depth image, we present a surveillance system of a certain area within Kinect's field of view. With computer vision library(Emgu CV), if an object is detected in the target area, it is tracked and kinect camera takes RGB image to send it in database server. Therefore, a mobile application on android platform was developed in order to notify the user that Kinect has sensed strange motion in the target region and display the RGB image of the scene. User gets the notification in real-time to react in the best way in the case of valuable things in monitored area or other cases related to a reserved zone.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.319-326
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• 2016

Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. In this paper, we propose a new Kinect camera-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The moving-pigs are labeled as regions of interest. 3) A contour method is proposed and applied to solve the touching-pigs problem in the Kinect-depth image. The experimental results with the depth videos obtained from a pig farm located in Sejong illustrate the efficiency of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.219-228
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• 2012

In this paper, we propose a paper keyboard piano implementation using the finger movement detection with the 3D image data from a kinect. Keyboard pattern and keyboard depth information are extracted from the color image and depth image to detect the touch event on the paper keyboard and to identify the touched key. Hand region detection error is unavoidable when using the simple comparison method between input depth image and background depth image, and this error is critical in key touch detection. Skin color is used to minimize the error. And finger tips are detected using contour detection with area limit and convex hull. Finally decision of key touch is carried out with the keyboard pattern information at the finger tip position. The experimental results showed that the proposed method can detect key touch with high accuracy. Paper keyboard piano can be utilized for the easy and convenient interface for the beginner to learn playing piano with the PC-based learning software.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.3
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• pp.343-350
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• 2014

Object recognition is one of the key technologies of the monitoring system for the prevention of crimes diversified the intelligent. The height is one of the physical information of the person, it may be important information to confirm the identity with physical characteristics of the subject has. In this paper, we provide a method of measuring the height that utilize RGB-Depth camera, the Kinect. Given that in order to measure the height of a person, and know the height of Kinect, by using the depth information of Kinect the distance to the head and foot of Kinect, estimating the height of a person. The proposed method throughout the experiment confirms that it is effective to estimate the height of a person in the room.