Traditionally, drivers rely on smartphones for GPS directions or locating nearby establishments. However, this reliance poses safety concerns as drivers divert their attention or type while on the road, contributing to fatal accidents. Voice-activated GPS systems integrated into newer vehicles attempted to mitigate these risks, but they falter in the presence of background noise.
Capio, with its unassuming black bar mounted on the car's dashboard equipped with camera and audio sensors, is revolutionizing the field of human-computer interaction. Lane's technology addresses the limitations of previous systems, utilizing computer vision-based approaches to track the movements and gestures of individuals within the car. This breakthrough enables the car to discern conversations between passengers and direct interactions with Capio.
The ultimate vision for contextually aware, human-computer interaction systems is a future where every interaction with machines feels as natural as conversing with another person. Capio sets the stage for this transformative future, offering hands-free, contextually aware interaction that not only addresses the issue of distracted driving but also empowers users to employ their hands in more meaningful ways. Spot an intriguing restaurant while on the road? A simple gesture and a query to Capio will provide information on its quality, drawing upon GPS data and an internet connection to pull up online reviews and recommend similar nearby establishments.
Furthermore, Capio's remarkable capabilities extend beyond mimicry. Leveraging deep learning systems, Capio learns and improves over time, akin to how children discern their parents' voices in a crowded room. By building upon its ability to identify individual voices, Capio enhances its accuracy through interactions with users.
Ian Lane, Jungsuk Kim, Tony L. Chen