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Improving Chamfer Template Matching Using Image Segmentation

delete2018-11-01
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PRE
AI
D
Duc Thanh Nguyen *
N
Ngoc‐Son Vu
T
Thanh-Toan Do
T
Thin Nguyen
J
John Yearwood
DOI:10.1109/LSP.2018.2862645delete
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摘要

摘要

En 中文
This letter proposes an effective method to improve object location in Chamfer template matching (CTM) based object detection using image segmentation. In our method, object bounding boxes are iteratively adjusted to fit with the object images obtained from image segmentation in a probabilistic model. The proposed method was tested with state-of-the-art CTM-based object detectors. Experimental results have shown the proposed method improved the location accuracy of the object detectors and reduce the false alarms rate.
Keyword:
Chamfer template matching (CTM)
image segmentation
object detection
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期刊

IEEE Signal Processing Magazine 封面图
IEEE Signal Processing Magazine
IF:
9.6
论文数:
1.1W
被引数:
1.7W

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U
University of Adelaide
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Australian Centre for Robotic Vision
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49
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Deakin University
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