A model of bottom-up visual attention using cortical magnification

Ala Aboudib (1, 2) , Vincent Gripon (1, 2) , Gilles Coppin (3, 4)

1 Lab-STICC_TB_CACS_IAS
2 ELEC - Département Electronique
3 Lab-STICC_TB_CID_IHSEV
4 DS - Direction Scientifique

The focus of visual attention has been argued to play a key role in object recognition. Many computational models of visual attention were proposed to estimate locations of eye fixations driven by bottom-up stimuli. Most of these models rely on pyramids consisting of multiple scaled versions of the visual scene. This design aims at capturing the fact that neural cells in higher visual areas tend to have larger receptive fields (RFs). On the other hand, very few models represent multi-scaling resulting from the eccentricity-dependent RF sizes within each visual layer, also known as the cortical magnification effect. In this paper, we demonstrate that using a cortical-magnification-like mechanism can lead to performant alternatives to pyramidal approaches in the context of attentional modeling. Moreover, we argue that introducing such a mechanism equips the proposed model with additional properties related to overt attention and distance-dependent saliency that are worth exploring.

Mots clés: Bottom-up saliency; Cortical magnification; Multi-scale; Visual attention

Domaines: Traitement des images [eess.IV]; Informatique; Traitement du signal et de l'image [eess.SP]; Electronique

Ala Aboudib, Vincent Gripon, Gilles Coppin. A model of bottom-up visual attention using cortical magnification. ICASSP 2015 : the 40th IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2015, Brisbane, Australia. pp.1493 - 1497. ⟨hal-01216084⟩