http://scholars.ntou.edu.tw/handle/123456789/7222
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Huang, R. J. | en_US |
dc.contributor.author | Tsao, C. Y. | en_US |
dc.contributor.author | Kuo, Y. P. | en_US |
dc.contributor.author | Lai, Y. C. | en_US |
dc.contributor.author | Liu, C. C. | en_US |
dc.contributor.author | Tu, Z. W. | en_US |
dc.contributor.author | Jung-Hua Wang | en_US |
dc.contributor.author | Chung-Cheng Chang | en_US |
dc.date.accessioned | 2020-11-20T07:04:44Z | - |
dc.date.available | 2020-11-20T07:04:44Z | - |
dc.date.issued | 2018-07-24 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | http://scholars.ntou.edu.tw/handle/123456789/7222 | - |
dc.description.abstract | Recently, an upsurge of deep learning has provided a new direction for the field of computer vision and visual tracking. However, expensive offline training time and the large number of images required by deep learning have greatly hindered progress. This paper aims to further improve the computational performance of CNT which is reported to deliver 5 fps performance in visual tracking, we propose a method called Fast-CNT which differs from CNT in three aspects: firstly, an adaptive k value (rather than a constant 100) is determined for an input video; secondly, background filters used in CNT are omitted in this work to save computation time without affecting performance; thirdly, SURF feature points are used in conjunction with the particle filter to address the drift problem in CNT. Extensive experimental results on land and undersea video sequences show that Fast-CNT outperforms CNT by 2~10 times in terms of computational efficiency. | en_US |
dc.language.iso | en | en_US |
dc.publisher | MDPI | en_US |
dc.relation.ispartof | Sensors | en_US |
dc.subject | visual tracking | en_US |
dc.subject | convolutional networks | en_US |
dc.subject | clustering | en_US |
dc.subject | IoT | en_US |
dc.subject | object detection | en_US |
dc.title | Fast Visual Tracking Based on Convolutional Networks | en_US |
dc.type | journal article | en_US |
dc.identifier.doi | <Go to ISI>://WOS:000445712400005 | - |
dc.identifier.doi | <Go to ISI>://WOS:000445712400005 | - |
dc.identifier.doi | 10.3390/s18082405 | - |
dc.identifier.doi | <Go to ISI>://WOS:000445712400005 | - |
dc.identifier.doi | <Go to ISI>://WOS:000445712400005 | - |
dc.identifier.url | <Go to ISI>://WOS:000445712400005 | - |
dc.relation.journalvolume | 18 | en_US |
dc.relation.journalissue | 8 | en_US |
item.openairetype | journal article | - |
item.fulltext | no fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.languageiso639-1 | en | - |
crisitem.author.dept | College of Electrical Engineering and Computer Science | - |
crisitem.author.dept | Department of Electrical Engineering | - |
crisitem.author.dept | National Taiwan Ocean University,NTOU | - |
crisitem.author.dept | College of Electrical Engineering and Computer Science | - |
crisitem.author.dept | Department of Electrical Engineering | - |
crisitem.author.dept | National Taiwan Ocean University,NTOU | - |
crisitem.author.dept | Center of Excellence for Ocean Engineering | - |
crisitem.author.dept | Data Analysis and Administrative Support | - |
crisitem.author.orcid | 0000-0002-8560-6030 | - |
crisitem.author.parentorg | National Taiwan Ocean University,NTOU | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | National Taiwan Ocean University,NTOU | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | National Taiwan Ocean University,NTOU | - |
crisitem.author.parentorg | Center of Excellence for Ocean Engineering | - |
Appears in Collections: | 電機工程學系 |
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