Université de Neuchâtel

AttentiRobot: A Visual Attention-based Landmark Selection Approach for Mobile Robot Navigation

Ouerhani, Nabil ; Hügli, Heinz ; Gruener, G. ; Codourey, A.

In: Proceedings. 2nd international workshop on attention and performance in computational vision (WAPCV), 2004, p. 1-7

Visual attention refers to the ability of a vision system to rapidly detect visually salient locations in a given scene. On the other hand, the selection of robust visual landmarks of an environment represents a cornerstone of reliable vision-based robot navigation systems. Indeed, can salient scene locations provided by visual attention be useful for robot navigation ? This work investigates the...

Université de Neuchâtel

Contribution of depth to visual attention: comparison of a computer model and human

Jost, Timothée ; Ouerhani, Nabil ; von Wartburg, Roman ; Müri, René ; Hügli, Heinz

In: Proceedings. Early cognitive vision workshop, 2004, p. 1-4

The research described in this paper aims at assessing the contribution of depth to visual attention. It reports the measurement of depth induced human visual attention derived from fixation patterns and preliminary results of a quantitative comparison with visual attention as modeled by different versions of a computational model. More specifically, a two-cues color model is compared to a...

Université de Neuchâtel

A Visual Attention-Based Approach for Automatic Landmark Selection and Recognition

Ouerhani, Nabil ; Hügli, Heinz ; Gruener, G. ; Codourey, A.

In: Attention and Performance in Computational Vision (In: Lecture Notes in Computer Science), 2005, vol. 3368, p. 183-195

Visual attention refers to the ability of a vision system to rapidly detect visually salient locations in a given scene. On the other hand, the selection of robust visual landmarks of an environment represents a cornerstone of reliable vision-based robot navigation systems. Indeed, can salient scene locations provided by visual attention be useful for robot navigation? This work investigates the...

Université de Neuchâtel

A Model of Dynamic Visual Attention for Object Tracking in Natural Image Sequences

Ouerhani, Nabil ; Hügli, Heinz

In: Computational Methods in Neural Modeling. In: Lecture Notes in Computer Science, 2003, vol. 2686, no. 1, p. 702-709

Visual attention is the ability to rapidly detect the interesting parts of a given scene on which higher level computer vision tasks can focus. This paper reports a computational model of dynamic visual attention which combines static and dynamic features to detect salient locations in natural image sequences. Therefore, the model computes a map of interest—saliency map—related to static...

Université de Neuchâtel

Model Performance for Visual Attention in Real 3D Color Scenes

Hügli, Heinz ; Jost, Timothée ; Ouerhani, Nabil

In: Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach. Series: Lecture Notes in Computer Science, 2006, vol. 3562, p. 469-478

Visual attention is the ability of a vision system, be it biological or artificial, to rapidly detect potentially relevant parts of a visual scene. The saliency-based model of visual attention is widely used to simulate this visual mechanism on computers. Though biologically inspired, this model has been only partially assessed in comparison with human behavior. The research described in this...

Université de Neuchâtel

Linear vs. Nonlinear Feature Combination for Saliency Computation: A Comparison with Human Vision

Ouerhani, Nabil ; Bur, Alexandre ; Hügli, Heinz

In: Pattern Recognition, Series: Lecture Notes in Computer Science, 2006, vol. 4174, p. 314-323

In the heart of the computer model of visual attention, an interest or saliency map is derived from an input image in a process that encompasses several data combination steps. While several combination strategies are possible and the choice of a method influences the final saliency substantially, there is a real need for a performance comparison for the purpose of model improvement. This paper...

Université de Neuchâtel

MAPS: Multiscale Attention-based Pre-Segmentation of Color Images

Ouerhani, Nabil ; Hügli, Heinz

In: Scale Space Methods in Computer Vision, 2003, vol. 2695, p. 537-549

Image segmentation is an essential preprocessing step towards scene understanding in computer vision. It consists in partitioning the image into connected regions which fulfill certain homogeneity criteria. Numerous segmentation techniques have been reported in the literature. Most of these techniques aim, however, at segmenting the entire image regardless of the relevance of each region....

Université de Neuchâtel

Robot Self-localization Using Visual Attention

Ouerhani, Nabil ; Hügli, Heinz

In: Proceedings. 6th IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), 2005, p. 309-314

This paper presents a robot self-localization method based on visual attention. This method takes advantage of the saliency-based model of attention to automatically learn configurations of salient visual landmarks along a robot path. During navigation, the visual attention algorithms detect a set of conspicuous visual features which are compared with the learned landmark configurations in order...

Université de Neuchâtel

Robot Navigation by Panoramic Vision and Attention Guided Features

Bur, A. ; Tapus, A. ; Ouerhani, Nabil ; Siegwar, R. ; Hügli, Heinz

In: Proceedings. 18th International Conference on Pattern Recognition (ICPR), 2006, vol. 1, p. 695-698

In visual-based robot navigation, panoramic vision emerges as a very attractive candidate for solving the localization task. Unfortunately, current systems rely on specific feature selection processes that do not cover the requirements of general purpose robots. In order to fulfil new requirements of robot versatility and robustness to environmental changes, we propose in this paper to perform...

Université de Neuchâtel

Assessing the contribution of color in visual attention

Jost, Timothée ; Ouerhani, Nabil ; von Wartburg, Roman ; Müri, René ; Hügli, Heinz

In: Computer Vision and Image Understanding, 2005, vol. 100, no. 1-2, p. 107-123

Visual attention is the ability of a vision system, be it biological or artificial, to rapidly detect potentially relevant parts of a visual scene, on which higher level vision tasks, such as object recognition, can focus. The saliency-based model of visual attention represents one of the main attempts to simulate this visual mechanism on computers. Though biologically inspired, this model has...