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Paste-and-Cut : Collective Image Localization and Classification for Real-Time Multi-Camera Object Detection
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Title
Paste-and-Cut : Collective Image Localization and Classification for Real-Time Multi-Camera Object Detection
DGIST Authors
Young Eun KangHoon Sung ChwaYeseong Kim
Advisor
좌훈승
Co-Advisor(s)
Yeseong Kim
Issued Date
2023
Awarded Date
2023-08-01
Citation
Young Eun Kang. (2023). Paste-and-Cut : Collective Image Localization and Classification for Real-Time Multi-Camera Object Detection. doi: 10.22677/THESIS.200000684351
Type
Thesis
Description
"Real-time systems"; "Object Detection"; "Neural Network"
Table Of Contents
Ⅰ.Introduction 1
Ⅱ.Related Work 5
Ⅲ.Target System and Motivation 7
3.1 Target System: DNN-based Object Detection 7
3.2 Feasibility of System Model 8
Ⅳ.System Design 12
4.1 System Goal and Overview 12
4.2 Merge-Canvas Size Decision Module 13
4.3 Localization Module: Paste 16
4.4 Classification Module: Cut 16
4.4.1 RoI Size Decision 17
4.4.2 Recursive Packing 18
Ⅴ. Evaluation 20
5.1 Experiment Setup 20
5.2 Experimental Results 21
5.2.1 Deadline Miss Ratio 21
5.2.2 Detection Accuracy 24
5.2.3 Execution time breakdown 27
Ⅵ. Conclusion 29
References 30
URI
http://hdl.handle.net/20.500.11750/46449
http://dgist.dcollection.net/common/orgView/200000684351
DOI
10.22677/THESIS.200000684351
Degree
Master
Department
Department of Electrical Engineering and Computer Science
Publisher
DGIST
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