Title:
Understanding Egocentric Activities
Understanding Egocentric Activities
Author(s)
Fathi, Alireza
Farhadi, Ali
Rehg, James M.
Farhadi, Ali
Rehg, James M.
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Abstract
We present a method to analyze daily activities, such
as meal preparation, using video from an egocentric camera.
Our method performs inference about activities, actions,
hands, and objects. Daily activities are a challenging
domain for activity recognition which are well-suited to an
egocentric approach. In contrast to previous activity recognition
methods, our approach does not require pre-trained
detectors for objects and hands. Instead we demonstrate
the ability to learn a hierarchical model of an activity by
exploiting the consistent appearance of objects, hands, and
actions that results from the egocentric context. We show
that joint modeling of activities, actions, and objects leads
to superior performance in comparison to the case where
they are considered independently. We introduce a novel
representation of actions based on object-hand interactions
and experimentally demonstrate the superior performance
of our representation in comparison to standard activity
representations such as bag of words.
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Date Issued
2011-11
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Text
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Proceedings