• 한국자동차공학회논문집
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• 제24권2호
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.

• 한국컴퓨터정보학회논문지
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• 제22권5호
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• pp.21-28
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• 2017

As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2004년도 International Conference on Digital Policy & Management
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• pp.185-202
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• 2004

Recent development in wireless computing and GPS technology cause the active development in the application system of location information in real-time environment such as transportation vehicle management, air traffic control and location based system. Especially, study about vehicle location tracking system, which monitors the vehicle's position in a control center, is appeared to be a representative application system. However, the current vehicle location tracking system can not provide vehicle position information that is not stored in a database at a specific time to users. We designed a vehicle location tracking system that could track vehicle location using mobile interface such as PDA. The proposed system consist of a vehicle location retrieving server and a mobile interface. It is provide not only the moving vehicle's current location but also the position at a past and future time which is not stored in database for users.

• 제어로봇시스템학회논문지
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• 제9권12호
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• pp.1033-1041
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• 2003

A new visual tracking scheme is proposed for a mobile robot that tracks a moving object in 3D space in real time. Visual tracking is to control a mobile robot to keep a moving target at the center of input image at all time. We made it possible by simplifying the relationship between the 2D image frame captured by a single camera and the 3D workspace frame. To precisely calculate the input vector (orientation and distance) of the mobile robot, the speed vector of the target is determined by eliminating the speed component caused by the camera motion from the speed vector appeared in the input image. The problem of temporary disappearance of the target form the input image is solved by selecting the searching area based on the linear prediction of target motion. The experimental results have shown that the proposed scheme can make a mobile robot successfully follow a moving target in real time.

• 방송공학회논문지
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• 제16권4호
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• pp.614-623
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• 2011

본 논문에서는 방송용 증강현실 시스템을 위한 실시간 카메라 추적 알고리듬을 제안한다. SURF(speeded up robust features) 알고리듬을 이용하여 추적을 초기화하며, 안정적인 실시간 카메라 추적을 위해 다층(multi-scale) 구조를 사용한다. 미리 알려져 있지 않고 시간에 따라 변하는 조명 환경에서의 특징 추적을 위해 정규상호상관도(normalized cross correlation, NCC)를 사용한다. 방송제작에는 줌 렌즈를 장착한 카메라가 사용되기 때문에 카메라의 초점거리를 온라인으로 추정할 필요가 있다. 카메라의 회전과 이동으로 이루어진 외부 포즈(pose) 변수와 함께 내부 변수인 초점거리를 목적함수에 포함시켜 함께 최적화한다. 실험결과는 제안한 온라인 카메라 보정 기법에 의해 카메라의 초점거리가 정확히 구해지는 것을 보여준다.

• 대한임베디드공학회논문지
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• 제10권6호
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• pp.363-372
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• 2015

Recent some SoC FPGA Releases that integrate ARM processor and FPGA fabric show better performance compared to the ASIC SoC used in typical embedded image processing system. In this study, using the above advantages, we implement a SoC FPGA-based Real-Time Object Recognition and Tracking System. In our system, the video input and output, image preprocessing process, and background subtraction processing were implemented in FPGA logics. And the object recognition and tracking processes were implemented in ARM processor-based programs. Our system provides the processing performance of 5.3 fps for the SVGA video input. This is about 79 times faster processing power than software approach based on the Nios II Soft-core processor, and about 4 times faster than approach based the HPS processor. Consequently, if the object recognition and tracking system takes a design structure combined with the FPGA logic and HPS processor-based processes of recent SoC FPGA Releases, then the real-time processing is possible because the processing speed is improved than the system that be handled only by the software approach.

• 한국통신학회논문지
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• 제32권4C호
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• pp.401-410
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• 2007

본 논문에서는 비젼 카메라와 다중 객체 추적 방법을 이용한 실시간 수질 감시 시스템을 제안하였다. 제안된 시스템은 기존의 센서 방식의 감시 시스템과 달리 비젼 카메라를 이용해 객체를 개별적으로 분석한다. 비젼 카메라를 이용한 시스템은 영상에서 개별 객체를 분리해 내는 방법과, 연속하는 두 프레임간의 상관관계에 의해서 다수의 객체를 추적하는 방법으로 구성된다. 실시간 처리를 위해 비모수 예측을 사용하여 배경 영상을 생성하고 이를 이용해 객체를 추출한다. 비모수 예측을 이용하면 연산량을 줄이는 동시에 비교적 정확하게 객체를 추출 할 수 있다. 다중 객체 추적 방법은 개별 객체가 움직이는 방향, 속도 및 가속도를 이용해 다음 움직임을 예측하고 이를 기반으로 추적을 수행하였다. 또한 추적 성공률을 향상시키기 위해 예외처리 알고리즘을 적용하였다. 다양한 환경에서 실험한 결과 제안한 시스템은 처리 시간이 짧고 정확하게 다중 객체를 추적할 수 있어 실시간 수질 감시 시스템에 사용이 가능함을 확인하였다.

• 한국멀티미디어학회논문지
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• 제16권11호
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• pp.1261-1271
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• 2013

Zoom tracking involves the automatic adjustment of the focus motor in response to the zoom motor movements for the purpose of keeping an object of interest in focus, and is typically achieved by moving the zoom and focus motors in a zoom lens module so as to follow the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. Thus, one can simply implement zoom tracking by following the most closest trace curve after all the trace curve data are stored in memory. However, this approach is often prohibitive in practical implementation because of its large memory requirement. Many other zoom tracking methods such as GZT, AZT and etc. have been proposed to avoid large memory requirement but with a deteriorated performance. In this paper, we propose a new zoom tracking method called 'Approximate Feedback Zoom Tracking method (AFZT)' on DM36x-based IP network camera, which does not need large memory by approximating nearby trace curves, but generates better zoom tracking accuracy than GZT or AZT by utilizing focus value as feedback information. Experiments through real implementation shows the proposed zoom tracking method improves the tracking performance and works in real-time.

• 방송공학회논문지
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• 제25권2호
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• pp.192-199
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• 2020

최근 딥러닝 모델을 기반으로 한 객체 추적 알고리즘의 활용도가 증가하고 있다. 영상에서의 다중 객체의 추적을 위한 시스템은 대표적으로 객체 검출 알고리즘과 객체 추적 알고리즘의 연쇄된 형태로 구성되어있다. 하지만 여러 모듈로 구성된 연쇄 형태의 시스템은 고성능 컴퓨팅 환경을 요구하며 실제 어플리케이션으로의 적용에 제한사항으로 존재한다. 본 논문에서는 위와 같은 객체 검출-추적의 연쇄 형태의 시스템에서 객체 검출 모듈의 연산 관련 프로세스를 조정하여 저성능 컴퓨팅 환경에서도 실시간 동작을 가능하게 하는 방법을 제안한다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2003년도 추계공동학술대회
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• pp.145-156
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• 2003

This paper for real time object tracking in this treatise detect histogram analysis that is accumulation value of binary conversion density and edge information and body that move by real time use of difference Image techniques and proposed method to object tracking. Firstly, we extract edge that can reduce quantity of data keeping information about form of input image in object detection. Object is extracted by performing difference image and binarization in edge image. Area of detected object is determined by threshold value that divide sum of horizontal accumulation value about binary conversion density by value that add horizontalityㆍverticality maximum accumulation value. Object is tracked by comparing similarity with object that is detected in previous frame and present frame. As experiment result, proposed algorithm could improve the object detection speed, and could track object by real time and could track local movement.