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Discovery of Activities via Statistical Clustering of Fixation PatternsHuman behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.
Document ID
20190004966
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Mulligan, Jeffrey B.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
May 3, 2019
Publication Date
January 13, 2019
Subject Category
Aerospace Medicine
Report/Patent Number
ARC-E-DAA-TN67820
Meeting Information
Meeting: Human Vision and Electronic Imaging 2019
Location: Burlingame, CA
Country: United States
Start Date: January 13, 2019
End Date: January 17, 2019
Sponsors: Society for Imaging Science and Technology
Funding Number(s)
WBS: 869021.03.01.01.04
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
NASA Technical Management
Keywords
Eye Movements
Pattern Analysis
Scan Path
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