Head-mounted mobile eye-tracking in the domestic dog: A new method

Abstract

Humans rely on dogs for countless tasks, ranging from companionship to highly specialized detection work. In their daily lives, dogs must navigate a human-built visual world, yet comparatively little is known about what dogs visually attend to as they move through their environment. Real-world eye-tracking, or head-mounted eye-tracking, allows participants to freely move through their environment, providing more naturalistic results about visual attention while interacting with objects and agents. In dogs, real-world eye-tracking has the potential to inform our understanding of cross-species cognitive abilities as well as working dog training; however, a robust and easily deployed head-mounted eye-tracking method for dogs has not previously been developed and tested. We present a novel method for real-world eye-tracking in dogs, using a simple head-mounted mobile apparatus mounted onto goggles designed for dogs. This new method, adapted from systems that are widely used in humans, allows for eye-tracking during more naturalistic behaviors, namely walking around and interacting with real-world stimuli, as well as reduced training time as compared to traditional stationary eye-tracking methods. We found that while completing a simple forced-choice treat finding task, dogs look primarily to the treat, and we demonstrated the accuracy of this method using alternative gaze-tracking methods. Additionally, eye-tracking revealed more fine-grained time course information and individual differences in looking patterns.

Keywords: Comparative cognition; Domestic dog; Eye-tracking; Visual attention.

Fig. 1

a A dog wearing size XL goggles, in full eye-tracking equipment during a trial. b A dog wearing size M goggles, in full the eye-tracking gear with the LCD screen that was removed during participation

Fig. 2

This full calibration procedure (a–f, seen here in the Yarbus software) is repeated at the start and end of each session. Each point provides known points where the gaze from the eye camera (top right) lines up to a specific known location from the scene camera’s field of view (as indicated by the yellow dots). The dog’s owner (g) immobilizes the head

Fig. 3

The test-calibration and verifier points allow for the identified center of gaze, shown here as a blue cursor, to be checked for spatial accuracy. A An example of a good calibration: the center of gaze is in the correct place, there are enough calibration points (indicated here by small yellow and blue dots) spread across the field of view. The next test-calibration point can now be verified. B An example of a poor and incomplete calibration: the center of gaze is offset from the known true gaze location (the treat), and the calibration does not have enough identified points (small yellow and blue dots). More calibration points must be included before verification can begin

Fig. 4

The six regions of interest coded during a trial from eye-tracking data. Room camera data were coded as falling into one of four ROIs, where ROIs 2 and 5 (treat-hand and treat-plate) and ROIs 3 and 6 (empty-hand and empty-plate) were combined to be coded as Treat or Empty, respectively

Fig. 5

A comparison of the data collected from the room camera (top) and the eye-tracking data (bottom) for a single trial. This demonstrates the finer spatial and temporal resolution of the eye-tracking data. Eye-tracking is able to capture rapid, shorter-duration looks. In addition, eye-tracking captures moments where the dog’s point of regard (where they are actually looking) differs from their head orientation, as observed from the room camera, like the glances off-target seen here in gray. See Supplementary Materials for video of this trial (https://osf.io/v8tdj/?view_only=2513d2cafc164586be7cf2fb580c5c0f)

Fig. 6

A comparison of the same moment in a trial from the two camera types. Left: Mid-trial data from the room camera. Tracking the head orientation from this angle suggests the dog is looking at the treat. Right. Mid-trial data from the eye-tracker. Using eye-tracking shows the dog was actually looking out the window

Fig. 7

The proportion of time during the observation phase (start of trial until dogs were released to make their choice) that dogs spent looking to the various ROIs. The five dogs in this sample displayed varying search strategies, with some dogs not looking at a given ROI at all (i.e., CCL485, who never looked at the experimenter’s hands after the treat presentation). Incorrect trials, indicated with overhead asterisks (*), do not display a consistent pattern of looks across dogs. Proportions graphs for the full trial (start of trial until choice) for each dog are available in the Supplementary Materials