Image Analytics:A consolidation of visual feature extraction methods  

作　　者：Xiaohui Liu Fei Liu Yijing Li Huizhang Shen Eric T.K.Lim Chee-Wee Tan 

机构地区：[1]Antai College of Economics and Management,Shanghai Jiao Tong University,Shanghai,People’s Republic of China [2]Department of Management and Marketing,Hong Kong Polytechnic University,Hongkong,People’s Republic of China [3]School of Information Systems and Technology Management,University of New South Wales,Sydney,Australia [4]Department of Digitization,Copenhagen Business School,Copenhagen,Denmark

出　　处：《Journal of Management Analytics》2021年第4期569-597,共29页管理分析学报（英文）

摘　　要：Revolutionary advances in machine and deep learning techniques within the field of computer field have dramatically expanded our opportunities to decipher the merits of digital imagery in the business world.Although extant literature on computer vision has yielded a myriad of approaches for extracting core attributes from images,the esotericism of the advocated techniques hinders scholars from delving into the role of visual rhetoric in driving business performance.Consequently,this tutorial aims to consolidate resources for extracting visual features via conventional machine and/or deep learning techniques.We describe resources and techniques based on three visual feature extraction methods,namely calculation-,recognition-,and simulation-based.Additionally,we offer practical examples to illustrate how image features can be accessed via open-sourced python packages such as OpenCV and TensorFlow.

关 键 词：Image analytics attribute extraction computer vision deep learning PYTHON 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]