DocumentCode :
595307
Title :
Do humans fixate on interest points?
Author :
Dave, Akshat ; Dubey, Richa ; Ghanem, Bernard
Author_Institution :
Nanyang Technol. Univ., Singapore, Singapore
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
2784
Lastpage :
2787
Abstract :
Interest point detectors (e.g. SIFT, SURF, and MSER) have been successfully applied to numerous applications in high level computer vision tasks such as object detection, and image classification. Despite their popularity, the perceptual relevance of these detectors has not been thoroughly studied. Here, perceptual relevance is meant to define the correlation between these point detectors and free-viewing human fixations on images. In this work, we provide empirical evidence to shed light on the fundamental question: “Do humans fixate on interest points in images?”. We believe that insights into this question may play a role in improving the performance of vision systems that utilize these interest point detectors. We conduct an extensive quantitative comparison between the spatial distributions of human fixations and automatically detected interest points on a recently released dataset of 1003 images. This comparison is done at both the global (image) level as well as the local (region) level. Our experimental results show that there exists a weak correlation between the spatial distributions of human fixation and interest points.
Keywords :
computer vision; feature extraction; image classification; object detection; transforms; MSER; SIFT; SURF; computer vision tasks; feature detection; feature extraction; free-viewing human fixations; image classification; interest point detectors; maximally stable extremal regions; object detection; scale-invariant feature transform; speeded-up robust features; vision systems; Correlation; Detectors; Distribution functions; Graphical models; Histograms; Humans; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460743
Link To Document :
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