Special faster-RCNN for multi-objects detection

Libin Hu D.V.M.; Changzhi Wei II; Xinghai Yang II; Teng Wang II

doi:10.1117/12.2501773

26 July 2018 Special faster-RCNN for multi-objects detection

Libin Hu D.V.M., Changzhi Wei II, Xinghai Yang II, Teng Wang II

Proceedings Volume 10828, Third International Workshop on Pattern Recognition; 108280W (2018) https://doi.org/10.1117/12.2501773
Event: Third International Workshop on Pattern Recognition, 2018, Jinan, China

Abstract

A series of neural networks called RCNN are playing a vital role in objects detection, as the most perfect one, Faster RCNN achieved an end-to-end object detection and made the detection times comparatively low but with high accuracy. In this work, we propose the following two changes to the original Faster RCNN model for multi-object detection: The first, we give 1800 ROI(Regions of Interest) comes from RPN to the RCNN network as input instead of 300, all the 1800 ROI are used to training the softmax classification and Bounding-box regression. The second, we traverse all xml files of every training image to get the number of marked objects and calculate the value of IOU for every marked objects, then we set a dynamic loss function to evaluation and optimization the Faster RCNN model by the two values of an image.

Citation Download Citation

Libin Hu D.V.M., Changzhi Wei II, Xinghai Yang II, and Teng Wang II "Special faster-RCNN for multi-objects detection", Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 108280W (26 July 2018); https://doi.org/10.1117/12.2501773

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available