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Several structural scene cues such as gist, layout, horizontal line, openness, and depth have been shown to guide scene perception (e.g., Oliva & Torralba, 2001); Ross & Oliva, 2009). Here, to investigate whether vanishing point (VP) plays a significant role in gaze guidance, we ran two experiments. In the first one, we recorded fixations of 10 observers (six male, four female; mean age 22; SD = 0.84) freely viewing 532 images, out of which 319 had a VP (shuffled presentation; each image for 4 s). We found that the average number of fixations at a local region (80 × 80 pixels) centered at the VP is significantly higher than the average fixations at random locations (t test; n = 319; p < 0.001). To address the confounding factor of saliency, we learned a combined model of bottom-up saliency and VP. The AUC (area under curve) score of our model (0.85; SD = 0.01) is significantly higher than the base saliency model (e.g., 0.8 using attention for information maximization (AIM) model by Bruce & Tsotsos, 2005, t test; p = 3.14e-16) and the VP-only model (0.64, t test; p < 0.001). In the second experiment, we asked 14 subjects (10 male, four female; mean age 23.07, SD = 1.26) to search for a target character (T or L) placed randomly on a 3 × 3 imaginary grid overlaid on top of an image. Subjects reported their answers by pressing one of the two keys. Stimuli consisted of 270 color images (180 with a single VP, 90 without). The target happened with equal probability inside each cell (15 times L, 15 times T). We found that subjects were significantly faster (and more accurate) when the target appeared inside the cell containing the VP compared to cells without the VP (median across 14 subjects 1.34 s vs. 1.96 s; Wilcoxon rank-sum test; p = 0.0014). These findings support the hypothesis that vanishing point, similar to face, text (Cerf, Frady, & Koch, 2009), and gaze direction Borji, Parks, & Itti, 2014) guides attention in free-viewing and visual search tasks.

Gaze direction provides an important and ubiquitous communication channel in daily behavior and social interaction of humans and some animals. While several studies have addressed gaze direction in synthesized simple scenes, few have examined how it can bias observer attention and how it might interact with early saliency during free viewing of natural and realistic scenes. Experiment 1 used a controlled, staged setting in which an actor was asked to look at two different objects in turn, yielding two images that differed only by the actor's gaze direction, to causally assess the effects of actor gaze direction. Over all scenes, the median probability of following an actor's gaze direction was higher than the median probability of looking toward the single most salient location, and higher than chance. Experiment 2 confirmed these findings over a larger set of unconstrained scenes collected from the Web and containing people looking at objects and/or other people. To further compare the strength of saliency versus gaze direction cues, we computed gaze maps by drawing a cone in the direction of gaze of the actors present in the images. Gaze maps predicted observers' fixation locations significantly above chance, although below saliency. Finally, to gauge the relative importance of actor face and eye directions in guiding observer's fixations, in Experiment 3, observers were asked to guess the gaze direction from only an actor's face region (with the rest of the scene masked), in two conditions: actor eyes visible or masked. Median probability of guessing the true gaze direction within ±9° was significantly higher when eyes were visible, suggesting that the eyes contribute significantly to gaze estimation, in addition to face region. Our results highlight that gaze direction is a strong attentional cue in guiding eye movements, complementing low-level saliency cues, and derived from both face and eyes of actors in the scene. Thus gaze direction should be considered in constructing more predictive visual attention models in the future.