The power of visual influence

The power of visual influence

image: The new approach determines a user’s real-time reaction to an image or scene based on their eye movement, in particular saccades, the super-fast eye movements that jump between points before fixing on an image or object. The researchers will demonstrate their new work titled “Image Features Influencing Reaction Time: A Probabilistic Learned Perceptual Model for Saccadic Latency” at SIGGRAPH 2022 on August 10. 8-11 in Vancouver, BC, Canada.
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Credit: ACM SIGGRAPH

What motivates or drives the human eye to fixate on a target and how, then, is that visual image perceived? What is the lag time between our visual acuity and our reaction to the observation? In the burgeoning field of immersive virtual reality (VR) and augmented reality (AR), connecting those dots, in real time, between eye movement, visual goals, and decision making is the driving force behind a new model. computational developed by a team. or computer scientists from New York University, Princeton University and NVIDIA.

The new approach determines a user’s real-time reaction to an image or scene based on their eye movement, particularly saccades, the super-fast eye movements that jump between points before fixing on an image or object. Saccadic movements allow frequent changes of attention to better understand the environment and locate objects of interest. Understanding the mechanism and behavior of saccades is vital to understanding human performance in visual environments, representing an exciting area of ​​research in computer graphics.

The researchers will demonstrate their new work titled “Image Features Influencing Reaction Time: A Probabilistic Learned Perceptual Model for Saccadic Latency” at SIGGRAPH 2022 on August 10. 8-11 in Vancouver, BC, Canada. The annual conference, which will be in-person and virtual this year, highlights the world’s leading professionals, academics and creative minds at the forefront of computer graphics and interactive techniques.

“Recently there has been extensive research to measure visual qualities perceived by humans, especially for VR/AR displays,” says the paper’s lead author, Qi Sun, PhD, assistant professor of computer science and engineering at the Tandon School of Engineering. from New York University.

“But we still need to explore how displayed content can influence our behavior, even in noticeable ways, and how we might use those displays to push boundaries of our performance that might not otherwise be possible.”

Drawing inspiration from how the human brain transmits data and makes decisions, the researchers implement a neurologically-inspired probabilistic model that mimics the accumulation of “cognitive trust” that leads to human decision and action. They conducted a psychophysical experiment with parameterized stimuli to observe and measure the correlation between image features and the time it takes to process them to trigger a saccadic movement, and whether the correlation differs from that of visual acuity.

They validate the model, using data from over 10,000 user experiment tests using an eye-tracking VR display, to understand and formulate the correlation between visual content and the “speed” of decision making based on the reaction to the image. The results show that the prediction of the new model accurately represents human behavior in the real world.

The proposed model can serve as a metric to predict and alter users’ eye image response time in interactive computer graphics applications, and can also help improve the design of virtual reality experiences and the performance of gamers. in esports. In other sectors, such as healthcare and automobiles, the new model could help estimate a doctor’s or driver’s ability to quickly respond and react to emergencies. In esports, it can be applied to measure the fairness of competition between players or to better understand how to maximize one’s performance when reaction times are down to milliseconds.

In future work, the team plans to explore the potential for cross-modal effects, such as visual and audio cues, that jointly affect our cognition in scenarios such as driving. They are also interested in expanding the work to better understand and represent the accuracy of human actions influenced by visual content.

The paper’s authors, Budmonde Duinkharjav (NYU); Praneeth Chakravarthula (Princeton); Rachel Brown (NVIDIA); Anjul Patney (NVIDIA); and Qi Sun (NYU), are set to demonstrate their new method on August 1. 11 at SIGGRAPH as part of the program, Round Table Session: Perception. The document can be found here.

About ACM SIGGRAPH
ACM SIGGRAPH is an international community of researchers, artists, developers, filmmakers, scientists, and business professionals with a shared interest in computer graphics and interactive techniques. As a special interest group of the Association for Computing Machinery (ACM), the world’s first and largest computing society, our mission is to nurture, champion, and connect like-minded researchers and practitioners to catalyze innovation in computer graphics and techniques. interactive.


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