NDLI: Deep learning-based real-time fine-grained pedestrian recognition using stream processing

Content Provider	IET Digital Library
Author	Zhang, Weishan Wang, Zhichao Liu, Xin Sun, Haoyun Zhou, Jiehan Liu, Yan Gong, Wenjuan
Abstract	Real-time recognition of pedestrian details can be very important in emergency situations for security reasons, such as traffic accidents identification from traffic video. However, this is challenging due to the needed accuracy of video data mining, and also the performance for real-time video processing. Here, the authors propose a solution for fine-grained pedestrian recognition in monitoring scenarios using deep learning and stream processing cloud computing, which is called DRPRS (deep learning-based real-time fine-grained pedestrian recognition using stream processing). The authors design an improved convolutional neural network (CNN) network called fine-CNN, which is a nine-layer neural network for detailed pedestrian recognition. In DRPRS, a pedestrian in a surveillance video is segmented and fine-grainedly recognised using improved single-shot detector and several fine-CNNs. DRPRS is supported by parallel mechanisms provided by Apache Storm stream processing framework. In addition, in order to further improve the recognition performance, a GPU-based scheduling algorithm is proposed to make full use of GPU resources in a cluster. The whole recognition process is deployed on a big video data processing platform to meet real-time requirements. DRPRS is extensively evaluated in terms of accuracy, fault tolerance, and performance, which show that the proposed approach is efficient.
Starting Page	602
Ending Page	609
Page Count	8
ISSN	1751956X
Volume Number	12
e-ISSN	17519578
Issue Number	Issue 7, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/12/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2017.0329
Journal	IET Intelligent Transport Systems
Publisher Date	2018-01-29
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Big Video Data Processing Platform Cloud Computing Cluster Computing Computer Vision And Image Processing Technique Deep Learning-based Real-time Fine-grained Pedestrian Recognition DRPRS Fine-CNN GPU-based Scheduling Algorithm Image Recognition Image Segmentation Improved Convolutional Neural Network Improved Single-shot Detector Knowledge Engineering Technique Learning in AI Neural Computing Technique Neural Nets Parallel Processing Parallel Software Pedestrian Real-time Video Processing Stream Processing Cloud Computing Surveillance Video Traffic Accidents Identification Traffic Engineering Computing Traffic Video Video Data Mining Video Signal Processing Video Surveillance
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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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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