Moving object tracking using fully convolutional neural network
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Moving object tracking using fully convolutional neural network
Moving object tracking using fully convolutional neural network
HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER THESIS Moving object tracking using Fully Convolutional neural networkQuang Minh Bui Minh.BQCBl 90097 Moving object tracking using fully convolutional neural network 7@sis.hust.edu. vn Control Engineering and AutomationSupervisor:PhD. Tran Thi ThaoSchool:School of Electrical EngineeringH ANOI, 4/2021AcknowlegementThis thesis is not possible without the inspiration and support of many people. I would liketo extend my appreciation toeveryone that has been a part o Moving object tracking using fully convolutional neural network f the journey.First and foremost. I would like to express my sincere gratitude to my research supervisors, Dr. Pham Van Truong and Dr. Tran Tlii ThaoMoving object tracking using fully convolutional neural network
at Hanoi University of Science and Technolog}’, for their consistent guidance, encouragement and supportive advises during the time I do my research. HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER THESIS Moving object tracking using Fully Convolutional neural networkQuang Minh Bui Minh.BQCBl 90097 Moving object tracking using fully convolutional neural network versity of Science and Technology for giving me the scholarship to encourage me in such a long journey. I would like to thank my colleagues at Viettel Corporation for their support in HPC related issues that boosted the progress of my work.AbstractVisual Object Tracking is one of the most fundamenta Moving object tracking using fully convolutional neural network l and critical task in computervision due to its wide range of usage in both civilian and military applications such as video surveillance, traffic moMoving object tracking using fully convolutional neural network
nitoring, autonomous vehicles,... The central problem of Visual Object Tracking is to precisely determine the position of an arbitrary object in a vidHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER THESIS Moving object tracking using Fully Convolutional neural networkQuang Minh Bui Minh.BQCBl 90097 Moving object tracking using fully convolutional neural network roblem, object tracking remains challenging due to the factors of many scenario such as occlusion, illumination change.This thesis proposes a novel method to solve those problem by adopting apprear-ance based object tracking approach empowering by deep features from Siamese networks. Siamese network Moving object tracking using fully convolutional neural network s put forward a simple framew-ork for trackingyet achieving remarkable performance in terms of the balance between accuracy- and speed. However, its pMoving object tracking using fully convolutional neural network
erformance degrades when suffering from fast target appearance changes due to its poor discrimination from other similar objects and clutter backgrounHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER THESIS Moving object tracking using Fully Convolutional neural networkQuang Minh Bui Minh.BQCBl 90097 Moving object tracking using fully convolutional neural network native capability of the trackers. We presents an improvement for Siamese networks by integrating the Convolutional Block Attention Module (CBAM) into the baseline. In which, attention plays a role not only to tell the model to concentrate on important features, but also neglecting distractor to enh Moving object tracking using fully convolutional neural network ance the represention of object of interest. As a result, the discriminative capability, adaptability and robustness of the tracker are increased. ExpMoving object tracking using fully convolutional neural network
erimental results on the two popular benchmarks 0TB2015 and VOT2O18 have shown that ourapproach achieved remarkable accuracy and robustness while mainHANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER THESIS Moving object tracking using Fully Convolutional neural networkQuang Minh Bui Minh.BQCBl 90097 Moving object tracking using fully convolutional neural network ablesviChapter 1: Introduction11.1Background..................................................11.1.1Challenges in visual object tracking..................21.1.2The general framework of visual object tracking.......31.2Motivation of this study....................................41-3 Contribution of T Moving object tracking using fully convolutional neural network hesis......................................51.4Outline.....................................................51.5Publications related to this research..Moving object tracking using fully convolutional neural network
.....................6Chapter 2: Literature Review72.1Classification of tracking methods..........................72.2Generative tracking methods.....HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER THESIS Moving object tracking using Fully Convolutional neural networkQuang Minh Bui Minh.BQCBl 90097 Moving object tracking using fully convolutional neural network .3Discriminative tracking methods............................122.3.1Traditional object trackers..........................13HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGYMASTER THESIS Moving object tracking using Fully Convolutional neural networkQuang Minh Bui Minh.BQCBl 90097Gọi ngay
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