NDLI: Feature channel enhancement for crowd counting

Content Provider	IET Digital Library
Author	Wu, Xingjiao Kong, Shuchen Zheng, Yingbin Ye, Hao Yang, Jing He, Liang
Abstract	Crowd counting, i.e. count the number of people in a crowded visual space, is emerging as an essential research problem with public security. A key in the design of the crowd counting system is to create a stable and accurate robust model, which requires to process on the feature channels of the counting network. In this study, the authors present a featured channel enhancement (FCE) block for crowd counting. First, they use a feature extraction unit to obtain the information of each channel and encodes the information of each channel. Then use a non-linear variation unit to deal with the encoded channel information, finally, normalise the data and affixed to each channel separately. With the use of the FCE, the positive characteristic channel can be enhanced and weak or negative channel information can be suppressed. The authors successfully incorporate the FCE with two compact networks on the standard benchmarks and prove that the proposed FCE achieves promising results.
Starting Page	2376
Ending Page	2382
Page Count	7
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 11, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.1308
Journal	IET Image Processing
Publisher Date	2020-04-02
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Accurate Robust Model Combinatorial Mathematics Computer Vision And Image Processing Technique Counting Network Crowd Counting System Crowded Visual Space Encoded Channel Information FCE Feature Channel Feature Channel Enhancement Feature Extraction Feature Extraction Unit Featured Channel Enhancement Block Fuzzy Set Theory Negative Channel Information Positive Characteristic Channel Stable Model Statistics Weak Channel Information
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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