• IEMEK Journal of Embedded Systems and Applications
• /
• v.10 no.6
• /
• pp.363-372
• /
• 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.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.162-167
• /
• 2003

In this paper, a novel feasible real-time system was researched for a differential driven wheeled autonomous mobile robot so that the mobile robot can move in a smooth, safe and elegant way. Least Square Minimum Path Planning was well used for the system to generate a smooth executable path for the mobile robot, and the point-to-point tracking algorithm was presented as well as its application in arbitrary path tracking. In order to make sure the robot can run elegantly and safely, trapezoidal speed was integrated into the point-to-point path tracking algorithm. The application to guest following for the autonomous mobile robot shows its wide application of the algorithm. The novel design was successfully proved to be feasible by our experiments on our mobile robot Interactive Robot Usher (IRU) in National University of Singapore.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.70.1-70
• /
• 2001

Recently, research of visual control is getting more essential in robotic application, and acquiring 3D informations from the 2D images is becoming more important with development of vision system. For this application, we propose the effective way of controlling stereo vision tracking system for target tracking and calculating distance between target and camera. In this paper we address improved controller using dual-loop visual servo which is more effective compared with using single-loop visual servo for stereo vision tracking system. The speed and the accuracy for realizing a real time tracking are important. However, the vision processing speed is too slow to track object in real time by using only vision feedback data. So we use another feedback data from controller parts which offer state feedback ...

• Transactions of the Korean Society of Automotive Engineers
• /
• v.24 no.2
• /
• pp.127-136
• /
• 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.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.4C
• /
• pp.401-410
• /
• 2007

In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.9
• /
• pp.39-48
• /
• 2009

Human face tracking has gradually become an important issue in applications for portable multimedia devices such as digital camcorder, digital still camera and cell phone. Current embedded face tracking software implementations lack the processing abilities to track faces in real time mobile video processing. In this paper, we propose a power efficient hardware-based face tracking architecture operating in real time. The proposed system was verified by FPGA prototyping and ASIC implementation using Samsung 65nm CMOS process. The implementation result shows that tracking speed is less than 8.4 msec with 150K gates and 20 mW average power consumption. Consequently it is validated that the proposed system is adequate for portable multimedia device.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.7
• /
• pp.34-42
• /
• 1999

Multi-target tracking system is defined as tracking several targets simultaneously. Kalman filter is widely used for target tracking problems. Kalman filter is known to be extremely useful as an optimal estimator but has a shortcoming of computational complexity. So a simplified estimator model which had less computational burden is proposed for a real-time implementation of multi-target tracking systems. In this paper, Kalman filter is applied to implement a real-time tracking system with a simplified target model. The proposed Kalman filter model is simpler compared with those of conventional ones, greatly reducing computation time, yet keeping the tracking abilities of the optimal Kalman filter. Through both simulations and experiments with real environments, it is demonstrated that the proposed simplified model works good in real situation with multiple to be tracked.

• Journal of Ubiquitous Convergence Technology
• /
• v.1 no.1
• /
• pp.3-8
• /
• 2007

This paper presents a set of techniques used in a real-time visual surveillance system. The system is implemented on a low-cost embedded DSP platform that is designed to work with stationary video sources. It consists of detection, a tracking and a classification module. The detector uses a statistical method to establish the background model and extract the foreground pixels. These pixels are grouped into blobs which are classified into single person, people in a group and other objects by the dynamic periodicity analysis. The tracking module uses mean shift algorithm to locate the target position. The system aims to control the human density in the surveilled scene and detect what happens abnormally. The major advantage of this system is the real-time capability and it only requires a video stream without other additional sensors. We evaluate the system in the real application, for example monitoring the subway entrance and the building hall, and the results prove the system's superior performance.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.1
• /
• pp.15-24
• /
• 2000

Stand-alone global position system receiver based on C/A code tracking generates position error of 100m mainly due to the selective availability and ionospheric and tropospheric delay errors. The differential GPS is the most commonly used method for removing those bias range error components. The relative GPS, although somewhat restrictive in its use, is ideally suited to the car monitoring system for improved Automatic Vehicle location, especially where the DGPS infrastructure is not available. The RGPS does not require any additional hardware, facility or external infrastructure and can be operated within the system with existing host computer and communication link. This paper presents detailed description of the RGPS concept and its implementation for real-time data processing. Performance of RGPS is evaluated with real data and is compared with DGPS.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.5
• /
• pp.21-28
• /
• 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.