FPGA Implementation of Edge-Guided Pattern Generation for Motion-Vector Estimation of Textureless Objects

被引：0

作者：

Tanibata, Aoi ^{[1
]}

Schmid, Alexandre ^{[2
]}

Takamaeda-Yamazaki, Shinya ^{[1
]}

Ikebe, Masayuki ^{[1
]}

Motomura, Masato ^{[1
]}

Asai, Tetsuya ^{[1
]}

机构：

[1] Hokkaido Univ, Grad Sch Informat Sci & Technol, Kita Ku, Kita 19,Nishi 9, Sapporo, Hokkaido 0600814, Japan

[2] Ecole Polytech Fed Lausanne, Microelect Syst Lab, CH-1015 Lausanne, Switzerland

来源：

2017 27TH INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS (FPL) | 2017年

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The widely accepted block-matching technique, which is required to identify motion vectors, fails in cases in which texture is not existent. In [1], we proposed a hardware-oriented cellular-automaton algorithm that generates spatial patterns on textureless objects and backgrounds, aiming at motion-vector estimation of textureless moving objects. This demonstration presents a field-programmable gate array (FPGA) system that supports real-time processing. This system provides motion-vectors in moving textureless objects and enables enhanced processing of motion vector classification.

引用

页数：1

共 2 条

[1] Motion Vector Estimation of Textureless Objects Exploiting Reaction-Diffusion Cellular Automata
Ushida, Miho
Schmid, Alexandre
Asai, Tetsuya
Ishimura, Kazuyoshi
Motomura, Masato
INTERNATIONAL JOURNAL OF UNCONVENTIONAL COMPUTING, 2016, 12 (2-3) : 169 - 187
[2] An Implementation of a 3D Image Filter for Motion Vector Generation on an FPGA Board
Chen, Yuchen
Wei, Kaijie
Nishi, Hiroaki
Amano, Hideharu
2022 TENTH INTERNATIONAL SYMPOSIUM ON COMPUTING AND NETWORKING, CANDAR, 2022, : 83 - 89

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