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object Detection-tracking algorithm for Unmanned Surface Vehicles Based on a Radar-Photoelectric System

IEEE ACCESS 2021年 9卷 57529-57541页

作者： Yu, Qingze Wang, Bo Su, Yumin Harbin Engn Univ Sci & Technol Underwater Vehicle Lab Harbin 150001 Peoples R China

object tracking is an important basis for the autonomous navigation of unmanned surface vehicles. However, several problems still must be addressed for a wide applicating of object tracking in unmanned surface vehicles. First, if multiple objects of the same classification exist in the same field of view, then stable extraction of an object is difficult. Second, in an environment with a complex background and large changes in object shape, the tracking accuracy is low, and object tracking errors and tracking loss can easily occur. Third, much time is required to detect a high-resolution real-time video stream, not meeting the delay requirement of the photoelectric servo stable tracking. To resolve these problems, this paper proposes an object detection-tracking algorithm based on a radar-photoelectric system. The algorithm combines an object detection algorithm with an object tracking algorithm and involves the following steps. First, a first-frame object extraction algorithm is used to extract the tracking object from the first frame. Second, a region of interest (ROI)-prediction algorithm is used to predict ROIs and detect objects in these ROIs. This algorithm can effectively solve the above problems in marine tests. When multiple objects of the same classification exist in the same field of view, the algorithm can extract the radar-guided object stably. When faced with a complex background and a large change in object shape, the algorithm substantially improves the accuracy and robustness of object tracking. Compared with the conventional object detection algorithm, the time consumption of this algorithm is reduced by 25.8%.

关键词： Radar tracking object tracking Prediction algorithms Correlation Filtering algorithms Classification algorithms Marine vehicles Unmanned surface vehicle radar-photoelectric system first-frame object extraction algorithm ROI-prediction algorithm object detection algorithm object tracking algorithm

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Enhancing the Performance of a Rainfall Measurement System Using Artificial Neural Networks Based object tracking algorithms

Enhancing the Performance of a Rainfall Measurement System U...

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IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

作者： Chen, Chih-Yen Wang, Lijuan Hwang, Chi-Hung Hsieh, Chi-Wen Chi, Po-Wei Natl Appl Res Labs Instrument Technol Res Ctr Hsinchu 30076 Taiwan Univ Kent Sch Engn & Digital Arts Canterbury CT2 7NT Kent England Natl Chiayi Univ Elect Engn Chiayi 60004 Taiwan

ISBN: (纸本)9781538634608

With the recent development of optical sensing and digital image processing techniques, high-speed cameras have been applied to measure the microphysical properties of raindrops. However, the performance of such systems arc significantly affected by object tracking algorithms. In order to improve the measurement accuracy of rainfall rate and accumulated rainfall, a novel object tracking algorithm based on artificial neural networks (ANN) is proposed in this paper. The ANN model takes the features of each raindrop in the two successive images as inputs including the center coordinates, area, canting angle, the lengths of long axis and minor axis of the equivalent ellipse. The output of the ANN model is the matched probabilities of each pair of raindrops between before and after images. Experimental data were collected during a real rainfall event. Performance comparisons between the traditional and ANN based object tracking algorithms are conducted based on the experimental data. Experimental results suggest the successful matching rate is significantly increased from 87.20% to 95.60% due to the usage of the ANN based algorithm. Hence, the improved disdrometer system is capable of producing more accurate and robust measurements of rainfall status.

关键词： rainfall measurement high-speed camera disdrometer object tracking algorithm artificial neural network

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Automatic aircraft extraction using video matting and frame registration

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IET IMAGE PROCESSING 2020年第8期14卷 1628-1635页

作者： Amin, Benish Mohsin Riaz, Muhammad Ghafoor, Abdul Natl Univ Sci & Technol Islamabad Pakistan COMSATS Ctr Adv Studies Telecommun Islamabad Pakistan

This study presents a technique to automatically extract the aircraft from video sequences. The technique incorporates object tracking algorithm to separate the region of interest (ROI), i.e. movement of aircraft, from video sequence, to reduce the computational complexity. Trimaps are generated automatically for given ROI using non-rigid image registration to obtain the prior information of the object and alpha mattes are estimated for each frame using KNN matting algorithm. However, the alpha matte of static region is estimated only once, that is combined with the alpha matte of moving region to generate final alpha matte. Simulations performed on different videos show that the proposed technique not only reduces the computational complexity, but also gives competitive results by generating high quality alpha maps.

关键词： feature extraction image sequences object detection image colour analysis image segmentation medical image processing image processing object tracking video signal processing image registration automatic aircraft extraction video matting video sequence object tracking algorithm computational complexity given ROI nonrigid image registration alpha mattes KNN matting algorithm static region final alpha matte different videos high quality alpha maps

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Seam tracking investigation via striped line laser sensor

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INDUSTRIAL ROBOT-AN INTERNATIONAL JOURNAL 2017年第5期44卷 609-617页

作者： Zou, Yanbiao Li, Jinchao Chen, Xiangzhi South China Univ Technol Sch Mech & Automot Engn Guangzhou Guangdong Peoples R China

Purpose - This paper aims to propose a set of six-axis robot arm welding seam tracking experiment platform based on Halcon machine vision library to resolve the curve seam tracking issue. Design/methodology/approach - Robot-based and image coordinate systems are converted based on the mathematical model of the three-dimensional measurement of structured light vision and conversion relations between robot-based and camera coordinate systems. An object tracking algorithm via weighted local cosine similarity is adopted to detect the seam feature points to prevent effectively the interference from arc and spatter. This algorithm models the target state variable and corresponding observation vector within the Bayes framework and finds the optimal region with highest similarity to the image-selected modules using cosine similarity. Findings - The paper tests the approach and the experimental results show that using metal inert-gas (MIG) welding with maximum welding current of 200A can achieve real-time accurate curve seam tracking under strong arc light and splash. Minimal distance between laser stripe and welding molten pool can reach 15 mm, and sensor sampling frequency can reach 50 Hz. Originality/value - Designing a set of six-axis robot arm welding seam tracking experiment platform with a system of structured light sensor based on Halcon machine vision library;and adding an object tracking algorithm to seam tracking system to detect image feature points. By this technology, this system can track the curve seam while welding.

关键词： Machine vision Welding Industrial robotics Seam tracking 3D measurement Line laser sensor object tracking algorithm

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An object-tracking algorithm Based on Particle Filtering with Region-Based Level Set Method

An Object-Tracking Algorithm Based on Particle Filtering wit...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Fei, Xianfeng Hashimoto, Koichi Tohoku Univ Grad Sch Informat Sci Aoba Ku Sendai Miyagi 9808579 Japan

ISBN: (纸本)9781424466757

In this paper, to realize robust tracking, we propose a particle filter (PF) model to track a single paramecium. The proposed PF model consists of a system dynamical model and an observation model. The information about our tracking object is described by a state vector and the system state is assumed to evolve according to the system dynamical model. The parallel region-based level set method with displacement correction (PR-LSM-DC) proposed in our previous work now works as the measurements for the PF model. The tracking is achieved by estimating the state of a moving object from the observations. Experiments show that with motion prediction using the PF model, we increase the robustness of tracking and extend the duration of single paramecium tracking. The 2 [ms] computational time indicates that we developed an algorithm and a computer aided system which achieves nonrigid single micro-organisms tracking in real-time as they deform, move and collide with others under optical microscope.

关键词： biology computer aided system displacement correction microorganisms nonrigid single microorganisms tracking object tracking object tracking algorithm optical microscope optical microscopes paramecium tracking particle filtering particle filtering (numerical methods) region based level set method

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A Simple Real-time object tracking System Based on small-scale VTOL UAV

A Simple Real-time Object Tracking System Based on small-sca...

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2014中国制导、导航与控制学术会议

作者： Runyang Zou Qiang Li Geng Wang Shanghai Jiao Tong University

ISBN: (纸本)9781479946983

There were many researches on UAVs,and in our case,we implemented a real-time tracking system with the camera on a VTOL UAV based on our tracking algorithm called BOM (Binary Outline Matching Method) which was different from CAMSHIFT [1] or optical flow [2].The UAV with our system could follow an object or track a specified path based on the object tracking algorithm and PID flight control.

关键词： aerospace control autonomous aerial vehicles cameras image sequences object tracking path planning three-term control BOM algorithm CAMSHIFT PID flight control binary outline matching method camera object tracking algorithm optical flow real-time object tracking system small-scale VTOL UAV Bills of materials Cameras Computer vision Educational institutions Image motion analysis object tracking Optical imaging

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A Novel object tracking algorithm Based On Point Pattern Matching

A Novel Object Tracking Algorithm Based On Point Pattern Mat...

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Second International Symposium on Information Science and Engineering(第二届信息科学与工程国际会议)

作者： Dan Li Baorong Xie Fan Mo Haodong Pei Wei Zhou Shuying Li Shanghai Institute of Technical Physics of The Chinese Academy of Sciences Shanghai China Shanghai Institute of Technical Physics of The Chinese Academy of Sciences Shanghai China

ISBN: (纸本)9781424463251

this paper proposes a novel point pattern matching algorithm. Compared with most published works, the proposed algorithm is characterized by its outstanding real time performance, making it the only applicable algorithm for object tracking among the existing ones. Evolved with the definition of point pattern matching, analyzing the object tracking task, it presents a specific description of the novel algorithm. The experimental results validate its real time performance and robustness.

关键词： point pattern matching object tracking algorithm

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