

FOLLOWUS
1School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
2Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
3Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
4School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611730, China
5Department of Electronic Engineering and Information Sciences, University of Science and Technology of China, Hefei 230027, China
6Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
7School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China
E-mail:yhtian@pku.edu.cn
E-mail:tjhuang@pku.edu.cn
Received:12 December 2016,
Accepted:26 December 2016,
Published:2017-01
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Yong-hong TIAN, Xi-lin CHEN, Hong-kai XIONG, et al. Towards human-like and transhuman perception in AI 2.0: a review[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 58-67.
Yong-hong TIAN, Xi-lin CHEN, Hong-kai XIONG, et al. Towards human-like and transhuman perception in AI 2.0: a review[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 58-67. DOI: 10.1631/FITEE.1601804.
感知是智能系统与现实世界的交互界面。如果没有复杂而灵活的感知能力,就不可能创造出高级的人工智能(Artificial intelligence
AI)系统。最近,潘云鹤院士提出了AI2.0的概念,其最重要的特征就是未来的AI系统应拥有类人甚至超人的智能感知能力。本文简要回顾了不同智能感知领域的研究现状,包括视觉感知、听觉感知、言语感知、感知信息处理与学习引擎等方面。在此基础上,论文对即将到来的AI 2.0时代智能感知领域需要大力研究发展的重点方向进行了展望,包括:(1)类人和超人的主动视觉;(2)自然声学场景的听知觉感知;(3)自然交互环境的言语感知及计算;(4)面向媒体感知的自主学习;(5)大规模感知信息处理与学习引擎;(6)城市全维度智能感知推理引擎。这些研究方向应在未来AI2.0的研究规划中进行重点布局。
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.
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