Regard estimation refers to the technology and methods used to predict the direction of a person’s gaze or where they are looking. This process typically involves analyser les mouvements oculaires and can be achieved through various techniques, including vision par ordinateur and apprentissage automatique.
At its core, gaze estimation relies on tracking the position and orientation of the eyes to infer the user’s focus point in their environment. This can be accomplished using specialized hardware, such as eye-tracking cameras, or through software algorithms that interpret images from standard cameras. The data collected can provide insights into user attention, engagement, and intent.
Il existe deux principaux types d'estimation du regard : screen-based and Estimation du regard en 3D. Screen-based systems are commonly used in research and marketing to analyze how users interact with digital interfaces. These systems can measure gaze on screens to assess how users navigate websites or applications. On the other hand, 3D gaze estimation is often employed in virtual reality (VR) and réalité augmentée (AR) environments, allowing for more immersive experiences by understanding where a user is looking within a three-dimensional space.
Gaze estimation has numerous applications across various fields, including psychology, l'interaction homme-machine, accessibility technology, and gaming. For example, it can help design more intuitive user interfaces, analyze consumer behavior, or assist individuals with disabilities in controlling devices with their gaze.
As technology advances, gaze estimation continues to improve in accuracy and efficiency, making it an essential tool for researchers and developers aiming to enhance expérience utilisateur et d'interaction.