Elastic Images by INRIA

The Elastic Images is a novel pseudo-haptic feedback technique which enables the perception of the local elasticity of images without the need of any haptic device. The proposed approach focus on whether visual feedback is able to induce a sensation of stiffness when the user interacts with an image using a standard mouse. The user, when clicking on a Elastic Image, is able to deform it locally according to its elastic properties. To reinforce the effect, we also propose the generation of procedural shadows and creases to simulate the compressibility of the image and several mouse cursors replacements to enhance pressure and stiffness perception. A psychophysical experiment was conducted to quantify this novel pseudo-haptic perception and determine its perceptual threshold (or its Just Noticeable Difference). The results showed that users were able to recognize up to eight different stiffness values with our proposed method and confirmed that it provides a perceivable and exploitable sensation of elasticity. The potential applications of the proposed approach range from pressure sensing in product catalogs and games, or its usage in graphical user interfaces for increasing the expressiveness of widgets.

Elastic Button

This work will be published and presented at the ACM Symposium on Applied Perception.

Pseudo-Haptic Textures by INRIA

Pseudo-haptic textures allow to optically-induce relief in textures without a haptic device by adjusting the speed of the mouse pointer according to the depth information encoded in the texture. In this work, we present a novel approach for using curvature information instead of relying on depth information. The curvature of the texture is encoded in a normal map which allows the computation of the curvature and local changes of orientation, according to the mouse position and direction. A user evaluation was conducted to compare the optically-induced haptic feedback of the curvature-based approach versus the original depth-based approach based on depth maps. Results showed that users, in addition to being able to efficiently recognize simulated bumps and holes with the curvature-based approach, were also able to discriminate shapes with lower frequency and amplitude.

This work was published and presented at Eurohaptics 2012. More information of this publication can be obtained at the following link.