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Main Authors: Yun, Heeseung, Gao, Ruohan, Ananthabhotla, Ishwarya, Kumar, Anurag, Donley, Jacob, Li, Chao, Kim, Gunhee, Ithapu, Vamsi Krishna, Murdock, Calvin
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2408.05364
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author Yun, Heeseung
Gao, Ruohan
Ananthabhotla, Ishwarya
Kumar, Anurag
Donley, Jacob
Li, Chao
Kim, Gunhee
Ithapu, Vamsi Krishna
Murdock, Calvin
author_facet Yun, Heeseung
Gao, Ruohan
Ananthabhotla, Ishwarya
Kumar, Anurag
Donley, Jacob
Li, Chao
Kim, Gunhee
Ithapu, Vamsi Krishna
Murdock, Calvin
contents Egocentric videos provide comprehensive contexts for user and scene understanding, spanning multisensory perception to behavioral interaction. We propose Spherical World-Locking (SWL) as a general framework for egocentric scene representation, which implicitly transforms multisensory streams with respect to measurements of head orientation. Compared to conventional head-locked egocentric representations with a 2D planar field-of-view, SWL effectively offsets challenges posed by self-motion, allowing for improved spatial synchronization between input modalities. Using a set of multisensory embeddings on a worldlocked sphere, we design a unified encoder-decoder transformer architecture that preserves the spherical structure of the scene representation, without requiring expensive projections between image and world coordinate systems. We evaluate the effectiveness of the proposed framework on multiple benchmark tasks for egocentric video understanding, including audio-visual active speaker localization, auditory spherical source localization, and behavior anticipation in everyday activities.
format Preprint
id arxiv_https___arxiv_org_abs_2408_05364
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Spherical World-Locking for Audio-Visual Localization in Egocentric Videos
Yun, Heeseung
Gao, Ruohan
Ananthabhotla, Ishwarya
Kumar, Anurag
Donley, Jacob
Li, Chao
Kim, Gunhee
Ithapu, Vamsi Krishna
Murdock, Calvin
Computer Vision and Pattern Recognition
Egocentric videos provide comprehensive contexts for user and scene understanding, spanning multisensory perception to behavioral interaction. We propose Spherical World-Locking (SWL) as a general framework for egocentric scene representation, which implicitly transforms multisensory streams with respect to measurements of head orientation. Compared to conventional head-locked egocentric representations with a 2D planar field-of-view, SWL effectively offsets challenges posed by self-motion, allowing for improved spatial synchronization between input modalities. Using a set of multisensory embeddings on a worldlocked sphere, we design a unified encoder-decoder transformer architecture that preserves the spherical structure of the scene representation, without requiring expensive projections between image and world coordinate systems. We evaluate the effectiveness of the proposed framework on multiple benchmark tasks for egocentric video understanding, including audio-visual active speaker localization, auditory spherical source localization, and behavior anticipation in everyday activities.
title Spherical World-Locking for Audio-Visual Localization in Egocentric Videos
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2408.05364