DOI
stands for Digital Object Identifier
(
D
igital
O
bject
I
dentifier
)
,
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.
Using DOI as a persistent link
To create a persistent link, add「http://dx.doi.org/」
「
http://dx.doi.org/
」
before a DOI.
For instance, if the DOI of an article is
10.5297/ser.1201.002
, you can link persistently to the article by entering the following link in your browser:
http://dx.doi.org/
10.5297/ser.1201.002
。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.
Cite a document with DOI
When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.
DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration ( doi.airiti.com ) 。
3D Object Detection and Pose Estimation from a Depth Image
郭皓淵 , Masters Advisor:賴尚宏
英文
DOI:
10.6843/NTHU.2014.00637
物體偵測 ; 姿態估測 ; 立體物件 ; Object Detection ; Pose Estimation ; 3D object


- [1] A. Patterson, P. Mordohai and K. Daniilidis, “Object Detection from Large-Scale 3D Datasets using Bottom-up and Top- down Descriptors,” ECCV 2008.
連結: - [2] A. Frome, D. Huber, R. Kolluri, T. Bulow, and J. Malik, “Recognizing Objects in Range Data Using Regional Point Descriptors,” ECCV 2004.
連結: - [3] H. Yokoyama, H. Date, S. Kanai and H. Takeda,” Detection and Classification of Pole- like Objects from Mobile Laser Scanning Data of Urban Environments,” ACDDE 2012.
連結: - [4] M. Lehtomaki, A. Jaakkola, J. Hyypp ¨ a, A. Kukko, H. Kaartinen, “Detection of Vertical Pole- Like Objects in a Road Environment Using Vehicle- Based Laser Scanning Data,” Remote Sensing 2010.
連結: - [5] B. Steder, G. Grisetti, M. V. Loock and W. Burgard, ” Robust On-line Model-based Object Detection from Range Images,” IROS 2009.
連結: