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A Sensor-based SLAM Algorithm for camera tracking in Virtual Studio

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International Journal of Automation and computing 2008年第2期5卷 152-162页

作者： Mansour Moniri Claude C.Chibelushi Faculty of Computing Engineering and TechnologyStaffordshire University

This paper addresses a sensor-based simultaneous localization and mapping （SLAM） algorithm for camera tracking in a virtual studio environment. The traditional camera tracking methods in virtual studios are vision-based or sensor-based. However, the chroma keying process in virtual studios requires color cues, such as blue background, to segment foreground objects to be inserted into images and videos. Chroma keying limits the application of vision-based tracking methods in virtual studios since the background cannot provide enough feature information. Furthermore, the conventional sensor-based tracking approaches suffer from the jitter, drift or expensive computation due to the characteristics of individual sensor system. Therefore, the SLAM techniques from the mobile robot area are first investigated and adapted to the camera tracking area. Then, a sensor-based SLAM extension algorithm for two dimensional （2D） camera tracking in virtual studio is described. Also, a technique called map adjustment is proposed to increase the accuracy＇ and efficiency of the algorithm. The feasibility and robustness of the algorithm is shown by experiments. The simulation results demonstrate that the sensor-based SLAM algorithm can satisfy the fundamental 2D camera tracking requirement in virtual studio environment.

关键词： Simultaneous localization and mapping (SLAM) particle filter chroma key camera tracking

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SEMI-AUTOMATIC INTERACTIVE MODELING FOR MODEL-BASED camera tracking

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SEMI-AUTOMATIC INTERACTIVE MODELING FOR MODEL-BASED CAMERA T...

A Sensor-Service Collaboration Approach for Target tracking in Wireless camera Networks

2012 3rd IEEE International Conference on Network Infrastructure and Digital Content

作者： Eun Joo Rhee Kangsoo Kim Byung-Kuk Seo Jong-Il Park Department of Electronics and Computer Engineering Hanyang UniversitySeoulKorea

Object modeling is an important task as a pre-processing of model-based camera *** this paper,we present a semi-automatic interactive modeling method to create 3D object models with simple primitives such as points and *** approach is based on feature-based modeling that uses 3D point clouds of target *** of using graphic modeling tools,the modeling is intuitively performed by user participation in video ***,we analyze sensitivity of camera tracking according to modeling errors using Cramer-Rao Lower Bound.

关键词： camera tracking Model-based tracking Object modeling Error analysis

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China Communications 2017年第7期14卷 44-56页

作者： Shuai Zhao Le Yu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China Mobile Information Security Center

Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource intensive and high-cost. camera tracking is an effective location tracking way for those emerging applications which can reuse the existing ubiquitous video monitoring system. This paper proposes a dynamic community-based camera collaboration(D3C) framework for target location and tracking. The contributions of D3C mainly include that(1) nonlinear perspective projection model is selected as the camera sensing model and sequential Monte Carlo is employed to predict the target location;(2) a dynamic collaboration scheme is proposed, it is based on the local community-detection theory deriving from social network analysis. The performance of proposed approach is validated by both synthetic datasets and real-world application. The experiment results show that D3C meets the versatility, real-time and fault tolerance requirements of target tracking applications.

关键词： service collaboration camera tracking community detection sequential monte carlo

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Survey of 3D modeling using depth cameras

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Virtual Reality & Intelligent Hardware 2019年第5期1卷 483-499页

作者： Hantong XU Jiamin XU Weiwei XU State Key Lab of CAD&CG Zhejiang UniversityHangzhou 310058China

Three-dimensional(3D)modeling is an important topic in computer graphics and computer *** recent years,the introduction of consumer-grade depth cameras has resulted in profound advances in 3D *** with the basic data structure,this survey reviews the latest developments of 3D modeling based on depth cameras,including research works on camera tracking,3D object and scene reconstruction,and high-quality texture *** also discuss the future work and possible solutions for 3D modeling based on the depth camera.

关键词： 3D Modeling Depth camera camera tracking Signed distance function Surfel

Augmented reality registration algorithm based on nature feature recognition

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Science China(Information Sciences) 2010年第8期53卷 1555-1565页

作者： CHEN Jing 1 , WANG YongTian 1,2 , GUO JunWei 1 , LIU Wei 1 , LIN JingDun 1 , XUE Kang 1 , LIU Yue 1 & DING GangYi 31 School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China 2 School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China 3 School of Software, Beijing Institute of Technology, Beijing 100081, China School of Optoelectronics Beijing Institute of Technology School of Computer Science and Technology Beijing Institute of Technology

This paper presents an improved key frame based augmented reality registration algorithm for real-time motion tracking in outdoor environment. In such applications, wide-baseline feature matching is a critical problem. In this paper, we apply randomized tree method to match key points extracted from the input image to those key frames as a classification problem. Extended Kalman filter is also utilized for jitter correction. A video see-through mobile augmented reality system is built for the on-site digital reconstruction of Yuanmingyuan Garden. Experimental results demonstrate that this algorithm is real-time, robust and effective for outdoor tracking.

关键词： outdoor augmented reality camera tracking randomized tree