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First-Person Action-Object Detection with EgoNet

Gedas Bertasius, Hyun Soo Park, Stella X. Yu, Jianbo Shi

Year
2017
Citations
44
Access
Open access

Abstract

Unlike traditional third-person cameras mounted on robots, a first-person camera, captures a person's visual sensorimotor object interactions from up close. In this paper, we study the tight interplay between our momentary visual attention and motor action with objects from a first-person camera. We propose a concept of action-objects-the objects that capture person's conscious visual (watching a TV) or tactile (taking a cup) interactions. Action-objects may be task-dependent but since many tasks share common person-object spatial configurations, action-objects exhibit a characteristic 3D spatial distance and orientation with respect to the person.

Keywords

Action (physics)Computer scienceObject (grammar)Artificial intelligenceComputer visionObject detectionHuman–computer interactionPattern recognition (psychology)

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