Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/623941
Title: NUS-PRO: A New Visual Tracking Challenge
Authors: Annan Li;Min Lin;Yi Wu;Ming-Hsuan Yang;Shuicheng Yan
subject: performance evaluation;Object tracking;benchmark database
Year: 2016
Publisher: IEEE
Abstract: Numerous approaches on object tracking have been proposed during the past decade with demonstrated success. However, most tracking algorithms are evaluated on limited video sequences and annotations. For thorough performance evaluation, we propose a large-scale database which contains 365 challenging image sequences of pedestrians and rigid objects. The database covers 12 kinds of objects, and most of the sequences are captured from moving cameras. Each sequence is annotated with target location and occlusion level for evaluation. A thorough experimental evaluation of 20 state-of-the-art tracking algorithms is presented with detailed analysis using different metrics. The database is publicly available and evaluation can be carried out online for fair assessments of visual tracking algorithms.
Description: 
URI: http://localhost/handle/Hannan/150979
http://localhost/handle/Hannan/623941
ISSN: 0162-8828
volume: 38
issue: 2
Appears in Collections:2016

Files in This Item:
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7072555.pdf1.44 MBAdobe PDFThumbnail
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Title: NUS-PRO: A New Visual Tracking Challenge
Authors: Annan Li;Min Lin;Yi Wu;Ming-Hsuan Yang;Shuicheng Yan
subject: performance evaluation;Object tracking;benchmark database
Year: 2016
Publisher: IEEE
Abstract: Numerous approaches on object tracking have been proposed during the past decade with demonstrated success. However, most tracking algorithms are evaluated on limited video sequences and annotations. For thorough performance evaluation, we propose a large-scale database which contains 365 challenging image sequences of pedestrians and rigid objects. The database covers 12 kinds of objects, and most of the sequences are captured from moving cameras. Each sequence is annotated with target location and occlusion level for evaluation. A thorough experimental evaluation of 20 state-of-the-art tracking algorithms is presented with detailed analysis using different metrics. The database is publicly available and evaluation can be carried out online for fair assessments of visual tracking algorithms.
Description: 
URI: http://localhost/handle/Hannan/150979
http://localhost/handle/Hannan/623941
ISSN: 0162-8828
volume: 38
issue: 2
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7072555.pdf1.44 MBAdobe PDFThumbnail
Preview File
Title: NUS-PRO: A New Visual Tracking Challenge
Authors: Annan Li;Min Lin;Yi Wu;Ming-Hsuan Yang;Shuicheng Yan
subject: performance evaluation;Object tracking;benchmark database
Year: 2016
Publisher: IEEE
Abstract: Numerous approaches on object tracking have been proposed during the past decade with demonstrated success. However, most tracking algorithms are evaluated on limited video sequences and annotations. For thorough performance evaluation, we propose a large-scale database which contains 365 challenging image sequences of pedestrians and rigid objects. The database covers 12 kinds of objects, and most of the sequences are captured from moving cameras. Each sequence is annotated with target location and occlusion level for evaluation. A thorough experimental evaluation of 20 state-of-the-art tracking algorithms is presented with detailed analysis using different metrics. The database is publicly available and evaluation can be carried out online for fair assessments of visual tracking algorithms.
Description: 
URI: http://localhost/handle/Hannan/150979
http://localhost/handle/Hannan/623941
ISSN: 0162-8828
volume: 38
issue: 2
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7072555.pdf1.44 MBAdobe PDFThumbnail
Preview File