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.