Open AccessPedestrians Detection of Offline Retail Stores Based on Computer Vision
Author(s) -
Mingxu Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1544/1/012120
Subject(s) - key (lock) , computer science , task (project management) , pedestrian detection , pedestrian , online and offline , object detection , artificial intelligence , identification (biology) , object (grammar) , core (optical fiber) , computer vision , pattern recognition (psychology) , computer security , transport engineering , engineering , telecommunications , botany , systems engineering , biology , operating system
Pedestrian Detection is a sub-task in the object detection due to it plays an important role in video surveillance. This project train model algorithm by using offline retail data and intelligent identification based on the offline retail brand store scene and focuses on the two core personnel of the retail scene-shopping guides and customers. This project detects pedestrian’s localization and their key points by using deep learning and computer vision technologies.