Human vision research aims at understanding the brain processes that enable us to see the world as a structured whole consisting of separate objects. To explain how humans organize a visual pattern, structural information theory starts from the idea that our visual system prefers the organization with the simplest descriptive code, that is, the code that captures a maximum of visual regularity....

Mental rotation in the congenitally blind was investigated with a haptic letter-judgment task. Blind subjects and blindfolded, sighted subjects were presented a letter in some orientation between 0° to 300° from upright and timed while they judged whether it was a normal or mirror-image letter. Both groups showed an increasing response time with the stimulus’s departure from upright; this resul...

A common assumption in neuroscience is that the visual system is adapted to the statistics of natural images [1]. Hence, by building probabilistic models of natural images, we can gain insight into how visual information is represented and processed in the visual cortex. For example, it has been shown that learning a sparse code for images predicts the shapes of simple cell receptive fields in ...

This paper proposes and evaluates interaction techniques for camera-equipped mobile phones. The proposed techniques are based on a visual code system that provides a number of orientation parameters, such as target pointing, rotation, tilting, distance, and relative movement. Our conceptual framework defines a set of fundamental physical gestures that form a basic vocabulary for describing inte...

Schema mappings are fundamental notions in data exchange and integration for relating source and target schemas. Visual mapping languages provide graphical means to visually describe such transformations. There is a plethora of tools and languages available however all use different notions and visualizations and are hardly extensible. In this paper we propose a new universal layer for schema m...

Learning programming can be a challenging task for design students, especially when code is to be entered in textual form. Visual programming languages, such as McNeil’s Grasshopper, have helped students to engage in scripting without having to deal with lower level syntax that is often hindering them in expressing their thoughts. However, the problem with learning how to program textually is o...

Neurons of the medial entorhinal cortex (MEC) provide spatial representations critical for navigation. In this network, the periodic firing fields of grid cells act as a metric element for position. The location of the grid firing fields depends on interactions between self-motion information, geometrical properties of the environment and nonmetric contextual cues. Here, we test whether visual ...

The visual system must reconstruct the three-dimensional structure of an object from two-dimensional retinal images. Previous research has shown that macaque inferior temporal (IT) neurons, although belonging to the ventral visual stream, code for depth defined by binocular disparity gradients. Here, we demonstrate that macaque IT neurons also code for depth defined by texture gradients, a mono...

We present images with binary codes in a way that balances discrimination and learnability of the codes. In our method, each image claims its own code in a way that maintains discrimination while being predictable from visual data. Category memberships are usually good proxies for visual similarity but should not be enforced as a hard constraint. Our method learns codes that maximize separabili...

Theoretical studies suggest that primary visual cortex (area V1) uses a sparse code to efficiently represent natural scenes. This issue was investigated by recording from V1 neurons in awake behaving macaques during both free viewing of natural scenes and conditions simulating natural vision. Stimulation of the nonclassical receptive field increases the selectivity and sparseness of individual ...