Design of Robust Multi-Template Tracking Based on a Multi-Layered Efficient Supervised Descent Prediction Algorithm

碩士 === 淡江大學 === 電機工程學系碩士班 === 106 === Planar object detection and tracking are important foundational techniques in augmented reality systems. In this thesis, an efficient and robust multi-template tracking method that includes multiple random-ferns planar detectors and real-time planar trackers is...

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Bibliographic Details
Main Authors: Kuang-Jui Hsu, 許光睿
Other Authors: Chi-Yi Tsai
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/s4vb2q