Showing papers on "Eye tracking published in 2011"

Robust Object Tracking with Online Multiple Instance Learning

Abstract: In this paper, we address the problem of tracking an object in a video given its location in the first frame and no other information. Recently, a class of tracking techniques called “tracking by detection” has been shown to give promising results at real-time speeds. These methods train a discriminative classifier in an online manner to separate the object from the background. This classifier bootstraps itself by using the current tracker state to extract positive and negative examples from the current frame. Slight inaccuracies in the tracker can therefore lead to incorrectly labeled training examples, which degrade the classifier and can cause drift. In this paper, we show that using Multiple Instance Learning (MIL) instead of traditional supervised learning avoids these problems and can therefore lead to a more robust tracker with fewer parameter tweaks. We propose a novel online MIL algorithm for object tracking that achieves superior results with real-time performance. We present thorough experimental results (both qualitative and quantitative) on a number of challenging video clips.

Robust Visual Tracking and Vehicle Classification via Sparse Representation

Abstract: In this paper, we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, noise, and other challenging issues are addressed seamlessly through a set of trivial templates. Specifically, to find the tracking target in a new frame, each target candidate is sparsely represented in the space spanned by target templates and trivial templates. The sparsity is achieved by solving an l1-regularized least-squares problem. Then, the candidate with the smallest projection error is taken as the tracking target. After that, tracking is continued using a Bayesian state inference framework. Two strategies are used to further improve the tracking performance. First, target templates are dynamically updated to capture appearance changes. Second, nonnegativity constraints are enforced to filter out clutter which negatively resembles tracking targets. We test the proposed approach on numerous sequences involving different types of challenges, including occlusion and variations in illumination, scale, and pose. The proposed approach demonstrates excellent performance in comparison with previously proposed trackers. We also extend the method for simultaneous tracking and recognition by introducing a static template set which stores target images from different classes. The recognition result at each frame is propagated to produce the final result for the whole video. The approach is validated on a vehicle tracking and classification task using outdoor infrared video sequences.

Context tracker: Exploring supporters and distracters in unconstrained environments

Abstract: Visual tracking in unconstrained environments is very challenging due to the existence of several sources of varieties such as changes in appearance, varying lighting conditions, cluttered background, and frame-cuts. A major factor causing tracking failure is the emergence of regions having similar appearance as the target. It is even more challenging when the target leaves the field of view (FoV) leading the tracker to follow another similar object, and not reacquire the right target when it reappears. This paper presents a method to address this problem by exploiting the context on-the-fly in two terms: Distracters and Supporters. Both of them are automatically explored using a sequential randomized forest, an online template-based appearance model, and local features. Distracters are regions which have similar appearance as the target and consistently co-occur with high confidence score. The tracker must keep tracking these distracters to avoid drifting. Supporters, on the other hand, are local key-points around the target with consistent co-occurrence and motion correlation in a short time span. They play an important role in verifying the genuine target. Extensive experiments on challenging real-world video sequences show the tracking improvement when using this context information. Comparisons with several state-of-the-art approaches are also provided.

Expertise Differences in the Comprehension of Visualizations: a Meta-Analysis of Eye-Tracking Research in Professional Domains

Abstract: This meta-analysis integrates 296 effect sizes reported in eye-tracking research on expertise differences in the comprehension of visualizations. Three theories were evaluated: Ericsson and Kintsch’s (Psychol Rev 102:211–245, 1995) theory of long-term working memory, Haider and Frensch’s (J Exp Psychol Learn Mem Cognit 25:172–190, 1999) information-reduction hypothesis, and the holistic model of image perception of Kundel et al. (Radiology 242:396–402, 2007). Eye movement and performance data were cumulated from 819 experts, 187 intermediates, and 893 novices. In support of the evaluated theories, experts, when compared with non-experts, had shorter fixation durations, more fixations on task-relevant areas, and fewer fixations on task-redundant areas; experts also had longer saccades and shorter times to first fixate relevant information, owing to superiority in parafoveal processing and selective attention allocation. Eye movements, reaction time, and performance accuracy were moderated by characteristics of visualization (dynamics, realism, dimensionality, modality, and text annotation), task (complexity, time-on-task, and task control), and domain (sports, medicine, transportation, other). These findings are discussed in terms of their implications for theories of visual expertise in professional domains and their significance for the design of learning environments.

Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking

Abstract: Applications for real-time visual tracking can be found in many areas, including visual odometry and augmented reality. Interest point detection and feature description form the basis of feature-based tracking, and a variety of algorithms for these tasks have been proposed. In this work, we present (1) a carefully designed dataset of video sequences of planar textures with ground truth, which includes various geometric changes, lighting conditions, and levels of motion blur, and which may serve as a testbed for a variety of tracking-related problems, and (2) a comprehensive quantitative evaluation of detector-descriptor-based visual camera tracking based on this testbed. We evaluate the impact of individual algorithm parameters, compare algorithms for both detection and description in isolation, as well as all detector-descriptor combinations as a tracking solution. In contrast to existing evaluations, which aim at different tasks such as object recognition and have limited validity for visual tracking, our evaluation is geared towards this application in all relevant factors (performance measures, testbed, candidate algorithms). To our knowledge, this is the first work that comprehensively compares these algorithms in this context, and in particular, on video streams.

Coregistration of eye movements and EEG in natural reading: analyses and review.

Abstract: Brain-electric correlates of reading have traditionally been studied with word-by-word presentation, a condition that eliminates important aspects of the normal reading process and precludes direct comparisons between neural activity and oculomotor behavior. In the present study, we investigated effects of word predictability on eye movements (EM) and fixation-related brain potentials (FRPs) during natural sentence reading. Electroencephalogram (EEG) and EM (via video-based eye tracking) were recorded simultaneously while subjects read heterogeneous German sentences, moving their eyes freely over the text. FRPs were time-locked to first-pass reading fixations and analyzed according to the cloze probability of the currently fixated word. We replicated robust effects of word predictability on EMs and the N400 component in FRPs. The data were then used to model the relation among fixation duration, gaze duration, and N400 amplitude, and to trace the time course of EEG effects relative to effects in EM behavior. In an extended Methodological Discussion section, we review 4 technical and data-analytical problems that need to be addressed when FRPs are recorded in free-viewing situations (such as reading, visual search, or scene perception) and propose solutions. Results suggest that EEG recordings during normal vision are feasible and useful to consolidate findings from EEG and eye-tracking studies.

Eye movements and perception: a selective review.

Abstract: Eye movements are an integral and essential part of our human foveated vision system. Here, we review recent work on voluntary eye movements, with an emphasis on the last decade. More selectively, we address two of the most important questions about saccadic and smooth pursuit eye movements in natural vision. First, why do we saccade to where we do? We argue that, like for many other aspects of vision, several different circuits related to salience, object recognition, actions, and value ultimately interact to determine gaze behavior. Second, how are pursuit eye movements and perceptual experience of visual motion related? We show that motion perception and pursuit have a lot in common, but they also have separate noise sources that can lead to dissociations between them. We emphasize the point that pursuit actively modulates visual perception and that it can provide valuable information for motion perception.

Real-time visual tracking using compressive sensing

Abstract: The l 1 tracker obtains robustness by seeking a sparse representation of the tracking object via l 1 norm minimization. However, the high computational complexity involved in the l 1 tracker may hamper its applications in real-time processing scenarios. Here we propose Real-time Com-pressive Sensing Tracking (RTCST) by exploiting the signal recovery power of Compressive Sensing (CS). Dimensionality reduction and a customized Orthogonal Matching Pursuit (OMP) algorithm are adopted to accelerate the CS tracking. As a result, our algorithm achieves a realtime speed that is up to 5,000 times faster than that of the l 1 tracker. Meanwhile, RTCST still produces competitive (sometimes even superior) tracking accuracy compared to the l 1 tracker. Furthermore, for a stationary camera, a refined tracker is designed by integrating a CS-based background model (CSBM) into tracking. This CSBM-equipped tracker, termed RTCST-B, outperforms most state-of-the-art trackers in terms of both accuracy and robustness. Finally, our experimental results on various video sequences, which are verified by a new metric — Tracking Success Probability (TSP), demonstrate the excellence of the proposed algorithms.

Accurate eye centre localisation by means of gradients

Abstract: The estimation of the eye centres is used in several computer vision applications such as face recognition or eye tracking. Especially for the latter, systems that are remote and rely on available light have become very popular and several methods for accurate eye centre localisation have been proposed. Nevertheless, these methods often fail to accurately estimate the eye centres in difficult scenarios, e.g. low resolution, low contrast, or occlusions. We therefore propose an approach for accurate and robust eye centre localisation by using image gradients. We derive a simple objective function, which only consists of dot products. The maximum of this function corresponds to the location where most gradient vectors intersect and thus to the eye’s centre. Although simple, our method is invariant to changes in scale, pose, contrast and variations in illumination. We extensively evaluate our method on the very challenging BioID database for eye centre and iris localisation. Moreover, we compare our method with a wide range of state of the art methods and demonstrate that our method yields a significant improvement regarding both accuracy and robustness.

Predictive remapping of attention across eye movements

Abstract: Many cells in retinotopic brain areas increase their activity when saccades (rapid eye movements) are about to bring stimuli into their receptive fields. Although previous work has attempted to look at the functional correlates of such predictive remapping, no study has explicitly tested for better attentional performance at the future retinal locations of attended targets. We found that, briefly before the eyes start moving, attention drawn to the targets of upcoming saccades also shifted to those retinal locations that the targets would cover once the eyes had moved, facilitating future movements. This suggests that presaccadic visual attention shifts serve to both improve presaccadic perceptual processing at the target locations and speed subsequent eye movements to their new postsaccadic locations. Predictive remapping of attention provides a sparse, efficient mechanism for keeping track of relevant parts of the scene when frequent rapid eye movements provoke retinal smear and temporal masking.

No clicks, no problem: using cursor movements to understand and improve search

Abstract: Understanding how people interact with search engines is important in improving search quality. Web search engines typically analyze queries and clicked results, but these actions provide limited signals regarding search interaction. Laboratory studies often use richer methods such as gaze tracking, but this is impractical at Web scale. In this paper, we examine mouse cursor behavior on search engine results pages (SERPs), including not only clicks but also cursor movements and hovers over different page regions. We: (i) report an eye-tracking study showing that cursor position is closely related to eye gaze, especially on SERPs; (ii) present a scalable approach to capture cursor movements, and an analysis of search result examination behavior evident in these large-scale cursor data; and (iii) describe two applications (estimating search result relevance and distinguishing good from bad abandonment) that demonstrate the value of capturing cursor data. Our findings help us better understand how searchers use cursors on SERPs and can help design more effective search systems. Our scalable cursor tracking method may also be useful in non-search settings.

Visual Attention in Objective Image Quality Assessment: Based on Eye-Tracking Data

Abstract: Since the human visual system (HVS) is the ultimate assessor of image quality, current research on the design of objective image quality metrics tends to include an important feature of the HVS, namely, visual attention. Different metrics for image quality prediction have been extended with a computational model of visual attention, but the resulting gain in reliability of the metrics so far was variable. To better understand the basic added value of including visual attention in the design of objective metrics, we used measured data of visual attention. To this end, we performed two eye-tracking experiments: one with a free-looking task and one with a quality assessment task. In the first experiment, 20 observers looked freely to 29 unimpaired original images, yielding us so-called natural scene saliency (NSS). In the second experiment, 20 different observers assessed the quality of distorted versions of the original images. The resulting saliency maps showed some differences with the NSS, and therefore, we applied both types of saliency to four different objective metrics predicting the quality of JPEG compressed images. For both types of saliency the performance gain of the metrics improved, but to a larger extent when adding the NSS. As a consequence, we further integrated NSS in several state-of-the-art quality metrics, including three full-reference metrics and two no-reference metrics, and evaluated their prediction performance for a larger set of distortions. By doing so, we evaluated whether and to what extent the addition of NSS is beneficial to objective quality prediction in general terms. In addition, we address some practical issues in the design of an attention-based metric. The eye-tracking data are made available to the research community .

The Oxford Handbook of Eye Movements

Abstract: THE EYE MOVEMENT REPERTOIRE NEURAL BASIS OF EYE MOVEMENTS VISUAL COGNITION AND EYE MOVEMENTS EYE MOVEMENT PATHOLOGY AND DEVELOPMENT EYE MOVEMENT CONTROL DURING READING LANGUAGE PROCESSING AND EYE MOVEMENTS

Head-Mounted Eye Tracking: A New Method to Describe Infant Looking

Abstract: Despite hundreds of studies describing infants’ visual exploration of experimental stimuli, researchers know little about where infants look during everyday interactions. The current study describes the first method for studying visual behavior during natural interactions in mobile infants. Six 14-month-old infants wore a head-mounted eye-tracker that recorded gaze during free play with mothers. Results revealed that infants’ visual exploration is opportunistic and depends on the availability of information and the constraints of infants’ own bodies. Looks to mothers’ faces were rare following infant-directed utterances but more likely if mothers were sitting at infants’ eye level. Gaze toward the destination of infants’ hand movements was common during manual actions and crawling, but looks toward obstacles during leg movements were less frequent.

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation

Abstract: MazeSuite is a complete toolset to prepare, present and analyze navigational and spatial experiments1. MazeSuite can be used to design and edit adapted virtual 3D environments, track a participants' behavioral performance within the virtual environment and synchronize with external devices for physiological and neuroimaging measures, including electroencephalogram and eye tracking. Functional near-infrared spectroscopy (fNIR) is an optical brain imaging technique that enables continuous, noninvasive, and portable monitoring of changes in cerebral blood oxygenation related to human brain functions2-7. Over the last decade fNIR is used to effectively monitor cognitive tasks such as attention, working memory and problem solving7-11. fNIR can be implemented in the form of a wearable and minimally intrusive device; it has the capacity to monitor brain activity in ecologically valid environments. Cognitive functions assessed through task performance involve patterns of brain activation of the prefrontal cortex (PFC) that vary from the initial novel task performance, after practice and during retention12. Using positron emission tomography (PET), Van Horn and colleagues found that regional cerebral blood flow was activated in the right frontal lobe during the encoding (i.e., initial naive performance) of spatial navigation of virtual mazes while there was little to no activation of the frontal regions after practice and during retention tests. Furthermore, the effects of contextual interference, a learning phenomenon related to organization of practice, are evident when individuals acquire multiple tasks under different practice schedules13,14. High contextual interference (random practice schedule) is created when the tasks to be learned are presented in a non-sequential, unpredictable order. Low contextual interference (blocked practice schedule) is created when the tasks to be learned are presented in a predictable order. Our goal here is twofold: first to illustrate the experimental protocol design process and the use of MazeSuite, and second, to demonstrate the setup and deployment of the fNIR brain activity monitoring system using Cognitive Optical Brain Imaging (COBI) Studio software15. To illustrate our goals, a subsample from a study is reported to show the use of both MazeSuite and COBI Studio in a single experiment. The study involves the assessment of cognitive activity of the PFC during the acquisition and learning of computer maze tasks for blocked and random orders. Two right-handed adults (one male, one female) performed 315 acquisition, 30 retention and 20 transfer trials across four days. Design, implementation, data acquisition and analysis phases of the study were explained with the intention to provide a guideline for future studies.

Eye Movement Monitoring as a Process Tracing Methodology in Decision Making Research

Abstract: Over the past half century, research on human decision making has expanded from a purely behaviorist approach that focuses on decision outcomes, to include a more cognitive approach that focuses on the decision processes that occur prior to the response. This newer approach, known as process tracing, has employed various methods, such as verbal protocols, information search displays, and eye movement monitoring, to identify and track psychological events that occur prior to the response (such as cognitive states, stages, or processes). In the present article, we review empirical studies that have employed eye movement monitoring as a process tracing method in decision making research, and we examine the potential of eye movement monitoring as a process tracing methodology. We also present an experiment that further illustrates the experimental manipulations and analysis techniques that are possible with modern eye tracking technology. In this experiment, a gaze-contingent display was used to manipulate stimulus exposure during decision making, which allowed us to test a specific hypothesis about the role of eye movements in preference decisions (the Gaze Cascade model; Shimojo, Simion, Shimojo, & Scheier, 2003). The results of the experiment did not confirm the predictions of the Gaze Cascade model, but instead support the idea that eye movements in these decisions reflect the screening and evaluation of decision alternatives. In summary, we argue that eye movement monitoring is a valuable tool for capturing decision makers’ information search behaviors, and that modern eye tracking technology is highly compatible with other process tracing methods such as retrospective verbal protocols and neuroimaging techniques, and hence it is poised to be an integral part of the next wave of decision research.

Gaze detection in a see-through, near-eye, mixed reality display

Abstract: The technology provides various embodiments for gaze determination within a see-through, near-eye, mixed reality display device. In some embodiments, the boundaries of a gaze detection coordinate system can be determined from a spatial relationship between a user eye and gaze detection elements such as illuminators and at least one light sensor positioned on a support structure such as an eyeglasses frame. The gaze detection coordinate system allows for determination of a gaze vector from each eye based on data representing glints on the user eye, or a combination of image and glint data. A point of gaze may be determined in a three-dimensional user field of view including real and virtual objects. The spatial relationship between the gaze detection elements and the eye may be checked and may trigger a re-calibration of training data sets if the boundaries of the gaze detection coordinate system have changed.

Gaze-independent brain-computer interfaces based on covert attention and feature attention.

Abstract: There is evidence that conventional visual brain?computer interfaces (BCIs) based on event-related potentials cannot be operated efficiently when eye movements are not allowed. To overcome this limitation, the aim of this study was to develop a visual speller that does not require eye movements. Three different variants of a two-stage visual speller based on covert spatial attention and non-spatial feature attention (i.e. attention to colour and form) were tested in an online experiment with 13 healthy participants. All participants achieved highly accurate BCI control. They could select one out of thirty symbols (chance level 3.3%) with mean accuracies of 88%?97% for the different spellers. The best results were obtained for a speller that was operated using non-spatial feature attention only. These results show that, using feature attention, it is possible to realize high-accuracy, fast-paced visual spellers that have a large vocabulary and are independent of eye gaze.

Eye gaze detection to determine speed of image movement

Abstract: A wearable computing device or a head-mounted display (HMD) may be configured to track the gaze axis of an eye of the wearer. In particular, the device may be configured to observe movement of a wearer's pupil and, based on the movement, determine inputs to a user interface. For example, using eye gaze detection, the HMD may change a tracking rate of a displayed virtual image based on where the user is looking. Gazing at the center of the HMD field of view may, for instance, allow for fine movements of the virtual display. Gazing near an edge of the HMD field of view may provide coarser movements.

Integrated eye tracking and display system

Abstract: Technology is provided for an integrated eye tracking and display system for a see-through, near-eye, mixed reality display device. Image data and IR illumination for eye tracking are optically coupled into a respective see-through, planar waveguide positioned to be seen through by each eye in a respective display optical system of the display device. The respective planar waveguide comprises one or more wavelength selective filters positioned to be co-axial with an optical axis of the respective display optical system. The wavelength selective filters direct IR and visible illumination out of the planar waveguide in the direction of the respective eye and direct IR reflections, including reflections from the eye, into the planar waveguide. The reflections are optically coupled out of the waveguide to an IR sensor which generates eye tracking data based on the reflections.

Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies

Abstract: Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies focuses on interactive communication and control tools based on gaze tracking, including eye typing, computer control, and gaming, with special attention to assistive technologies. For researchers and practitioners interested in the applied use of gaze tracking, the book offers instructions for building a basic eye tracker from off-the-shelf components, gives practical hints on building interactive applications, presents smooth and efficient interaction techniques, and summarizes the results of effective research on cutting edge gaze interaction applications.

Eye tracker based contextual action

Abstract: The present invention relates to systems and methods for assisting a user when interacting with a graphical user interface by combining eye based input with input for e.g. selection and activation of objects and object parts and execution of contextual actions related to the objects and object parts. The present invention also relates to such systems and methods in which the user can configure and customize specific combinations of eye data input and input that should result in a specific contextual action.

Eye movements and visual expertise in chess and medicine

Abstract: The chapter highlights the theoretical and applied contributions of eye movement research to the study of human expertise. Using examples drawn from the domains of chess and medicine, the chapter demonstrates that eye movements arc particularly well-suited for studying two hallmarks of expert performance: the superior perceptual encoding of domain related patterns, and experts' tacit (or implicit) domain related knowledge. Specifically, eye movement findings indicate that expertise is associated with a greater ability to process domain related visual information in terms of larger patterns of features rather than isolated features. Furthermore, in support of the role of tacit knowledge in expertise, there is evidence that the eye movements of experts may contain informarion that is not consciously accessible.

Does it make a difference if I have an eye contact with you or with your picture? An ERP study

Abstract: Several recent studies have begun to examine the neurocognitive mechanisms involved in perceiving and responding to eye contact, a salient social signal of interest and readiness for interaction. Laboratory experiments measuring observers' responses to pictorial instead of live eye gaze cues may, however, only vaguely approximate the real-life affective significance of gaze direction cues. To take this into account, we measured event-related brain potentials and subjective affective responses in healthy adults while viewing live faces with a neutral expression through an electronic shutter and faces as pictures on a computer screen. Direct gaze elicited greater face-sensitive N170 amplitudes and early posterior negativity potentials than averted gaze or closed eyes, but only in the live condition. The results show that early-stage processing of facial information is enhanced by another person's direct gaze when the person is faced live. We propose that seeing a live face with a direct gaze is processed more intensely than a face with averted gaze or closed eyes, as the direct gaze is capable of intensifying the feeling of being the target of the other's interest and intentions. These results may have implications for the use of pictorial stimuli in the social cognition studies.

Systems and methods for high-resolution gaze tracking

Abstract: A system mounted within eyewear or headwear to unobtrusively produce and track reference locations on the surface of one or both eyes of an observer is provided to improve the accuracy of gaze tracking. The system utilizes multiple illumination sources and/or multiple cameras to generate and observe glints from multiple directions. The use of multiple illumination sources and cameras can compensate for the complex, three-dimensional geometry of the head and the significant anatomical variations of the head and eye region that occurs among individuals. The system continuously tracks the initial placement and any slippage of eyewear or headwear. In addition, the use of multiple illumination sources and cameras can maintain high-precision, dynamic eye tracking as an eye moves through its full physiological range. Furthermore, illumination sources placed in the normal line-of-sight of the device wearer increase the accuracy of gaze tracking by producing reference vectors that are close to the visual axis of the device wearer.

Evaluation of Traditional, Orthogonal, and Radial Tree Diagrams by an Eye Tracking Study

Abstract: Node-link diagrams are an effective and popular visualization approach for depicting hierarchical structures and for showing parent-child relationships. In this paper, we present the results of an eye tracking experiment investigating traditional, orthogonal, and radial node-link tree layouts as a piece of empirical basis for choosing between those layouts. Eye tracking was used to identify visual exploration behaviors of participants that were asked to solve a typical hierarchy exploration task by inspecting a static tree diagram: finding the least common ancestor of a given set of marked leaf nodes. To uncover exploration strategies, we examined fixation points, duration, and saccades of participants' gaze trajectories. For the non-radial diagrams, we additionally investigated the effect of diagram orientation by switching the position of the root node to each of the four main orientations. We also recorded and analyzed correctness of answers as well as completion times in addition to the eye movement data. We found out that traditional and orthogonal tree layouts significantly outperform radial tree layouts for the given task. Furthermore, by applying trajectory analysis techniques we uncovered that participants cross-checked their task solution more often in the radial than in the non-radial layouts.

Object co-occurrence serves as a contextual cue to guide and facilitate visual search in a natural viewing environment.

Abstract: There is accumulating evidence that scene context can guide and facilitate visual search (e.g., A. Torralba, A. Oliva, M. S. Castelhano, & J. M. Henderson, 2006). Previous studies utilized stimuli of restricted size, a fixed head position, and context defined by the global spatial configuration of the scene. Thus, it is unknown whether similar effects generalize to natural viewing environments and to context defined by local object co-occurrence. Here, with a mobile eye tracker, we investigated the effects of object co-occurrence on search performance under naturalistic conditions. Observers searched for low-visibility target objects on tables cluttered with everyday objects. Targets were either located adjacent to larger, more visible "cue" objects that they regularly co-occurred in natural scenes (expected condition) or elsewhere in the display, surrounded by unrelated objects (unexpected condition). Mean search times were shorter for targets at expected locations as compared to unexpected locations. Additionally, context guided eye movements, as more fixations were directed toward cue objects than other non-target objects, particularly when the cue was contextually relevant to the current search target. These results could not be accounted for by image saliency models. Thus, we conclude that object co-occurrence can serve as a contextual cue to facilitate search and guide eye movements in natural environments.