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Complex motion modeling and State Estimation in Road Coordinates

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Journal of Harbin Institute of Technology(New Series) 2017年第1期24卷 19-25页

作者： Keyi Li Xi Chen Gongjian Zhou School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

Constrained modeling and state estimation have attracted much attention in recent years. This paper focuses on target motion modeling and tracking in road coordinates. An improved initialization method,which uses the optimal fusion of the position measurements in different directions,is presented for the constraint coordinate Kalman filter(CCKF). The CCKF is evaluated with a comprehensive comparison to the state-of-art linear equality constraint estimation methods. Numerical simulation results demonstrate the better performance of the CCKF. Then the interacting multiple model CCKF(IMM-CCKF) is proposed to manifest the advantages of the CCKF in complex motion modeling and state estimations. The effectiveness of the IMM-CCKF in maneuvering target tracking with spatial equality constraints is demonstrated by numerical experiments.

关键词： Ground Targets motion modeling Road Constraints Initialization IMM

Real-time tracking of fast-moving object in occlusion scene

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Journal of Systems Engineering and Electronics 2024年第3期35卷 741-752页

作者： LI Yuran LI Yichen ZHANG Monan YU Wenbin GUAN Xinping Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Systems Control and Information Processing Ministry of Education of ChinaShanghai 200240China

Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.

关键词： speed-accuracy balanced motion modeling constrained updater

Rolling Shutter Camera:modeling,Optimization and Learning

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Machine Intelligence Research 2023年第6期20卷 783-798页

作者： Bin Fan Yuchao Dai Mingyi He School of Electronics and Information Northwestern Polytechnical UniversityXi’an710129China

Most modern consumer-grade cameras are often equipped with a rolling shutter mechanism,which is becoming increasingly important in computer vision,robotics and autonomous driving ***,its temporal-dynamic imaging nature leads to the rolling shutter effect that manifests as geometric *** the years,researchers have made significant progress in developing tractable rolling shutter models,optimization methods,and learning approaches,aiming to remove geometry distortion and improve visual *** this survey,we review the recent advances in rolling shutter cameras from two aspects of motion modeling and deep *** the best of our knowledge,this is the first comprehensive survey of rolling shutter *** the part of rolling shutter motion modeling and optimization,the principles of various rolling shutter motion models are elaborated and their typical applications are ***,the applications of deep learning in rolling shutter based image processing are ***,we conclude this survey with discussions on future research directions.

关键词： Rolling shutter motion modeling image correction temporal super-resolution deep learning

Research on Hydrodynamics Model Test for Deepsea Open-Framed Remotely Operated Vehicle

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China Ocean Engineering 2012年第2期26卷 329-339页

作者：范士波连琏任平 State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Chinese Underwater Technology Institute Shanghai Jiao Tong University

This paper presents the features of newly designed hydrodynamics test for the scaled model of 4500 m deepsea open-framed remotely operated vehicle （ROV）, which is being researched and developed by Shanghai Jiao Tong University. Accurate hydrodynamics coefficients measurement and spatial modeling of ROV are significant for the maneuverability and control algorithm. The scaled model of ROV was constructed by 1：1.6. Hydrodynamics coefficients were measured through VPMM and LAHPMM towing test. And dynamics model was derived as a set of equations, describing nonlinear and coupled 5-DOF spatial motions. Rotation control motion was simulated to verify spatial model proposed. Research and application of hydrodynamics coefficients are expected to enable ROV to overcome uncertainty and disturbances of deepsea environment, and accomplish some more challengeable and practical missions.

关键词： Remotely Operated Vehicle (ROV) model test hydrodynamics coefficients motion modeling