Madeline H. Pelgrim, Shreyas Sundara Raman, Thomas Serre, Daphna Buchsbaum
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引用次数: 0
Abstract
Dogs have a unique evolutionary relationship with humans, yet little is known about the visual information available to them or how they direct their visual attention within their environment. The present study, inspired by comparable work in infants, classified the items available to be gazed at by dogs during a common daily event, a walk. We then explored the statistics over the availability of those categories and over the dogs’ visual attention. Using a head-mounted eye-tracking apparatus that was custom-designed for dogs, 11 dogs walked on a predetermined route outdoors under naturalistic conditions generating a total of 11,698 gazes for analysis. Image stills from these fixations were analyzed using computer vision techniques to explore the items present, the space within the visual field those items occupied, and which of the items the dog was gazing at. On average, dogs looked proportionally most at buses, plants, people, the pavement, and construction equipment; however, there were significant individual differences. The results of this project provide a foundational step toward understanding how dogs look at and interact with their physical world, opening up avenues for future research into how they learn and make decisions, both independently and with a human social partner.
期刊介绍:
Cognitive Science publishes articles in all areas of cognitive science, covering such topics as knowledge representation, inference, memory processes, learning, problem solving, planning, perception, natural language understanding, connectionism, brain theory, motor control, intentional systems, and other areas of interdisciplinary concern. Highest priority is given to research reports that are specifically written for a multidisciplinary audience. The audience is primarily researchers in cognitive science and its associated fields, including anthropologists, education researchers, psychologists, philosophers, linguists, computer scientists, neuroscientists, and roboticists.