自我中心和外中心方法:一个简短的调查

IF 3.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Anirudh Thatipelli , Shao-Yuan Lo , Amit K. Roy-Chowdhury
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引用次数: 0

摘要

自我中心视觉从相机佩戴者的角度捕捉场景,而外心视觉捕捉整个场景背景。共同建模自我和exo视图对于开发下一代人工智能代理至关重要。社区重新对自我中心视野产生了兴趣。虽然第三人称视角和第一人称视角已经得到了深入的研究,但很少有作品旨在同时研究两者。外心视频包含许多相关信号,这些信号可以转移到自我中心视频中。本文对自我中心与外中心视野相结合的研究成果进行了综述,这是一个非常新颖但很有前景的研究课题。我们详细描述了数据集,并对ego-exo联合学习的关键应用进行了调查,其中我们确定了最新的进展。根据目前的进展情况,我们相信这个简短而及时的调查将对广泛的视频理解社区有价值,特别是在多视图建模至关重要的时候。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Egocentric and exocentric methods: A short survey
Egocentric vision captures the scene from the point of view of the camera wearer while exocentric vision captures the overall scene context. Jointly modeling ego and exo views is crucial to developing next-generation AI agents. The community has regained interest in the field of egocentric vision. While the third-person view and first-person have been thoroughly investigated, very few works aim to study both synchronously. Exocentric videos contain many relevant signals that are transferrable to egocentric videos. This paper provides a timely overview of works combining egocentric and exocentric visions, a very new but promising research topic. We describe in detail the datasets and present a survey of the key applications of ego-exo joint learning, where we identify the most recent advances. With the presentation of the current status of the progress, we believe this short but timely survey will be valuable to the broad video-understanding community, particularly when multi-view modeling is critical.
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来源期刊
Computer Vision and Image Understanding
Computer Vision and Image Understanding 工程技术-工程:电子与电气
CiteScore
7.80
自引率
4.40%
发文量
112
审稿时长
79 days
期刊介绍: The central focus of this journal is the computer analysis of pictorial information. Computer Vision and Image Understanding publishes papers covering all aspects of image analysis from the low-level, iconic processes of early vision to the high-level, symbolic processes of recognition and interpretation. A wide range of topics in the image understanding area is covered, including papers offering insights that differ from predominant views. Research Areas Include: • Theory • Early vision • Data structures and representations • Shape • Range • Motion • Matching and recognition • Architecture and languages • Vision systems
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