Towards human-like and transhuman perception in AI 2.0:a review

作     者：Yong-hong TIAN Xi-lin CHEN Hong-kai XIONG Hong-liang LI Li-rong DAI Jing CHEN Jun-liang XING Xi-hong WU Wei-min HU Yu HU Tie-jun HUANG Wen GAO Yong-hong TIAN;Xi-lin CHEN;Hong-kai XIONG;Hong-liang LI;Li-rong DAI;Jing CHEN;Jun-liang XING;Jing CHEN;Xi-hong WU;Wei-min HU;Yu HU;Tie-jun HUANG;Wen GAO

作者机构：School of Electronics Engineering and Computer SciencePeking University Institute of Computing TechnologyChinese Academy of Sciences Department of Electronic EngineeringShanghai Jiao Tong University School of Electronic EngineeringUniversity of Electronic Science and Technology of China Department of Electronic Engineering and Information SciencesUniversity of Science and Technology of China School of OptoelectronicsBeijing Institute of Technology Institute of AutomationChinese Academy of Sciences 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2017年第18卷第1期

页      面：58-67页

核心收录：

学科分类：0710[理学-生物学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 071006[理学-神经生物学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Strategic Consulting Research Project of Chinese Academy of Engineering(No.2016-ZD-04-03) 

主　　题：Intelligent perception Active vision Auditory perception Speech perception Autonomous learning 

摘      要：Perception is the interaction interface between an intelligent system and the real world. Without sophisticated and flexible perceptual capabilities, it is impossible to create advanced artificial intelligence （AI） systems. For the next-generation AI, called ＇AI 2.0＇, one of the most significant features will be that AI is empowered with intelligent perceptual capabilities, which can simulate human brain＇s mechanisms and are likely to surpass human brain in terms of performance. In this paper, we briefly review the state-of-the-art advances across different areas of perception, including visual perception, auditory perception, speech perception, and perceptual information processing and learning engines. On this basis, we envision several R＆D trends in intelligent perception for the forthcoming era of AI 2.0, including： （1） human-like and transhuman active vision; （2） auditory perception and computation in an actual auditory setting; （3） speech perception and computation in a natural interaction setting; （4） autonomous learning of perceptual information; （5） large-scale perceptual information processing and learning platforms; and （6） urban omnidirectional intelligent perception and reasoning engines. We believe these research directions should be highlighted in the future plans for AI 2.0.