Vidhya Navalpakkam

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We propose a computational model for the task-specific guidance of visual attention in real-world scenes. Our model emphasizes four aspects that are important in biological vision: determining task-relevance of an entity, biasing attention for the low-level visual features of desired targets, recognizing these targets using the same low-level features, and(More)
How does a visual search goal modulate the activity of neurons encoding different visual features (e.g., color, direction of motion)? Previous research suggests that goal-driven attention enhances the gain of neurons representing the target's visual features. Here, we present mathematical and behavioral evidence that this strategy is suboptimal and that(More)
Integration of goal-driven, top-down attention and image-driven, bottom-up attention is crucial for visual search. Yet, previous research has mostly focused on models that are purely top-down or bottom-up. Here, we propose a new model that combines both. The bottom-up component computes the visual salience of scene locations in different feature maps(More)
Web Search has seen two big changes recently: rapid growth in mobile search traffic, and an increasing trend towards providing answer-like results for relatively simple information needs (e.g., [weather today]). Such results display the answer or relevant information on the search page itself without requiring a user to click. While clicks on organic search(More)
Previous experiments have shown that human attention is influenced by high level task demands. In this paper, we propose an architecture to estimate the task-relevance of attended locations in a scene. We maintain a task graph and compute relevance of fixations using an ontology that contains a description of real world entities and their relationships. Our(More)
Although much is known about the sources and modulatory effects of top-down attentional signals, the information capacity of these signals is less known. Here, we investigate the granularity of top-down attentional signals. Previous theories in psychophysics have provided conflicting evidence on whether top-down guidance is coarse grained (i.e., one gain(More)
As search pages are becoming increasingly complex, with images and nonlinear page layouts, understanding how users examine the page is important. We present a lab study on the effect of a rich informational panel to the right of the search result column, on eye and mouse behavior. Using eye and mouse data, we show that the flow of user attention on(More)
The ability to choose rapidly among multiple targets embedded in a complex perceptual environment is key to survival. Targets may differ in their reward value as well as in their low-level perceptual properties (e.g., visual saliency). Previous studies investigated separately the impact of either value or saliency on choice; thus, it is not known how the(More)
The ability to search efficiently for a target in a cluttered environment is one of the most remarkable functions of the nervous system. This task is difficult under natural circumstances, as the reliability of sensory information can vary greatly across space and time and is typically a priori unknown to the observer. In contrast, visual-search experiments(More)
Survival in the natural world demands the selection of relevant visual cues to rapidly and reliably guide attention towards prey and predators in cluttered environments. We investigate whether our visual system selects cues that guide search in an optimal manner. We formally obtain the optimal cue selection strategy by maximizing the signal to noise ratio(More)