Journal article
Combining Low and Mid-Level Gaze Features for Desktop Activity Recognition
Namrata Srivastava, Joshua Newn, E Velloso
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies | Association for Computing Machinery (ACM) | Published : 2018
DOI: 10.1145/3287067
Abstract
Human activity recognition (HAR) is an important research area due to its potential for building context-aware interactive systems. Though movement-based activity recognition is an established area of research, recognising sedentary activities remains an open research question. Previous works have explored eye-based activity recognition as a potential approach for this challenge, focusing on statistical measures derived from eye movement properties---low-level gaze features---or some knowledge of the Areas-of-Interest (AOI) of the stimulus---high-level gaze features. In this paper, we extend this body of work by employing the addition of mid-level gaze features; features that add a level of ..
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