348 research outputs found
The contributions of foveal versus extrafoveal vision to visual search in real-world scenes:Evidence from eye movements
Zum Zusammenhang von Familiensoziologie und Familiendemografie seit 1945 in der Bundesrepublik Deutschland
-Germany, Germany/FRG
Eye guidance during real-world scene search:The role color plays in central and peripheral vision
The visual system utilizes environmental features to direct gaze efficiently when locating objects. While previous research has isolated various features' contributions to gaze guidance, these studies generally used sparse displays and did not investigate how features facilitated search as a function of their location on the visual field. The current study investigated how features across the visual field-particularly color-facilitate gaze guidance during real-world search. A gaze-contingent window followed participants' eye movements, restricting color information to specified regions. Scene images were presented in full color, with color in the periphery and gray in central vision or gray in the periphery and color in central vision, or in grayscale. Color conditions were crossed with a search cue manipulation, with the target cued either with a word label or an exact picture. Search times increased as color information in the scene decreased. A gaze-data based decomposition of search time revealed color-mediated effects on specific subprocesses of search. Color in peripheral vision facilitated target localization, whereas color in central vision facilitated target verification. Picture cues facilitated search, with the effects of cue specificity and scene color combining additively. When available, the visual system utilizes the environment's color information to facilitate different real-world visual search behaviors based on the location within the visual field
Object-based saccadic selection during scene perception:Evidence from viewing position effects
CRISP: a computational model of fixation durations in scene viewing
Eye-movement control during scene viewing can be represented as a series of individual decisions about where and when to move the eyes. While substantial behavioral and computational research has been devoted to investigating the placement of fixations in scenes, relatively little is known about the mechanisms that control fixation durations. Here, we propose a computational model (CRISP) that accounts for saccade timing and programming and thus for variations in fixation durations in scene viewing. First, timing signals are modeled as continuous-time random walks. Second, difficulties at the level of visual and cognitive processing can inhibit and thus modulate saccade timing. Inhibition generates moment-by-moment changes in the random walk’s transition rate and processing-related saccade cancellation. Third, saccade programming is completed in 2 stages: an initial, labile stage that is subject to cancellation and a subsequent, nonlabile stage. Several simulation studies tested the model’s adequacy and generality. An initial simulation study explored the role of cognitive factors in scene viewing by examining how fixation durations differed under different viewing task instructions. Additional simulations investigated the degree to which fixation durations were under direct moment-to-moment control of the current visual scene. The present work further supports the conclusion that fixation durations, to a certain degree, reflect perceptual and cognitive activity in scene viewing. Computational model simulations contribute to an understanding of the underlying processes of gaze control
Was ging in ihm vor? Laientheorien über kognitive und emotionale Vorgänge eines Selbstmörders
Tested Rational-Emotive Behavior Therapy’s (REBT; Ellis, 1962, 1994) assumption that irrational beliefs and maladaptive emotions are associated with dysfunctional behaviors, whereas rational cognitions and adaptive emotions lead to functional actions. Participants read newspaper articles about the defeat of a boxer. In one condition, the (authentic) article informed participants that he committed suicide, and in a second (fictitious) article about the same defeat, the athlete was described as successfully resuming his career. Participants’ assumptions about the stimulus person’s defeat-related cognitions and emotions were assessed on rating scales and via sentence completion and free responses. Participants responding to the suicide scenario assumed significantly more irrational beliefs (e.g., ”I absolutely have to win”) on the side of the boxer regarding his defeat than controls in the fictitious non-suicide version. This finding was obtained by all assessment methods. Additionally, participants expected the suicidal stimulus person to be experiencing maladaptive emotions (e.g., depression, guilt), whereas the stimulus person who successfully resumed his career was expected to experience adaptive affects (e.g., sadness, concern). Subsequent ratings of the functionality of selected emotions revealed that sadness, fear, annoyance, and concern were rated to be more functional than depression, anxiety, rage, and guilt.In einer Fragebogenstudie wurden den Teilnehmenden reale Zeitungsartikel vorgelegt, die vom Selbstmord eines besiegten Boxers berichteten. Die Probanden sollten sich in die Person des Sportlers hineinversetzen und die Gedanken und Gefühle schildern, die sie bei ihm in Zusammenhang mit der Niederlage erwarteten. Die Probanden vermuteten bei dem Sportler durchgängig in höherer Weise irrationale rigide Gedanken (z.B. „ich muss unbedingt siegen“) als rationales Denken (z.B. „ich möchte gerne siegen“) und eher maladaptive Emotionen (Angst, Wut, Depression und Schuld) als adaptive Emotionen (Furcht, Ärger, Trauer und Bedauern). Dies trat jedoch nur dann ein, wenn in den Zeitungsartikeln nachfolgendes dysfunktionales Verhalten des Boxers (Suizid) geschildert wurde: In einer Kontrollbedingung, die ebenfalls von der Niederlage – allerdings mit erfolgreicher Fortsetzung der Boxerkarriere – berichtet, zeigte sich dieses Datenmuster nicht. Diese Befunde entsprechen den theoretischen Annahmen und Vorhersagen der Rational-Emotiven-Verhaltenstherapie (REVT) von Albert Ellis. Zusätzlich erhobene Daten zur generellen Funktionalität der acht Emotionen bestätigen ebenfalls die theoretischen Annahmen
New Young Star Candidates in BRC 27 and BRC 34
We used archival Spitzer Space Telescope mid-infrared data to search for
young stellar objects (YSOs) in the immediate vicinity of two bright-rimmed
clouds, BRC 27 (part of CMa R1) and BRC 34 (part of the IC 1396 complex). These
regions both appear to be actively forming young stars, perhaps triggered by
the proximate OB stars. In BRC 27, we find clear infrared excesses around 22 of
the 26 YSOs or YSO candidates identified in the literature, and identify 16 new
YSO candidates that appear to have IR excesses. In BRC 34, the one
literature-identified YSO has an IR excess, and we suggest 13 new YSO
candidates in this region, including a new Class I object. Considering the
entire ensemble, both BRCs are likely of comparable ages, within the
uncertainties of small number statistics and without spectroscopy to confirm or
refute the YSO candidates. Similarly, no clear conclusions can yet be drawn
about any possible age gradients that may be present across the BRCs.Comment: 54 pages, 19 figures, accepted by A
Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics
Dozens of new models on fixation prediction are published every year and
compared on open benchmarks such as MIT300 and LSUN. However, progress in the
field can be difficult to judge because models are compared using a variety of
inconsistent metrics. Here we show that no single saliency map can perform well
under all metrics. Instead, we propose a principled approach to solve the
benchmarking problem by separating the notions of saliency models, maps and
metrics. Inspired by Bayesian decision theory, we define a saliency model to be
a probabilistic model of fixation density prediction and a saliency map to be a
metric-specific prediction derived from the model density which maximizes the
expected performance on that metric given the model density. We derive these
optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC,
NSS, CC, SIM, KL-Div) and show that they can be computed analytically or
approximated with high precision. We show that this leads to consistent
rankings in all metrics and avoids the penalties of using one saliency map for
all metrics. Our method allows researchers to have their model compete on many
different metrics with state-of-the-art in those metrics: "good" models will
perform well in all metrics.Comment: published at ECCV 201
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