Results 1 - 10
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39
The contributions of color to recognition memory for natural scenes
- Journal of Experimental Psychology: Learning, Memory and Cognition
, 2002
"... The authors used a recognition memory paradigm to assess the influence of color information on visual memory for images of natural scenes. Subjects performed 5%–10 % better for colored than for blackand-white images independent of exposure duration. Experiment 2 indicated little influence of contras ..."
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Cited by 23 (1 self)
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The authors used a recognition memory paradigm to assess the influence of color information on visual memory for images of natural scenes. Subjects performed 5%–10 % better for colored than for blackand-white images independent of exposure duration. Experiment 2 indicated little influence of contrast once the images were suprathreshold, and Experiment 3 revealed that performance worsened when images were presented in color and tested in black and white, or vice versa, leading to the conclusion that the surface property color is part of the memory representation. Experiments 4 and 5 exclude the possibility that the superior recognition memory for colored images results solely from attentional factors or saliency. Finally, the recognition memory advantage disappears for falsely colored images of natural scenes: The improvement in recognition memory depends on the color congruence of presented images with learned knowledge about the color gamut found within natural scenes. The results can be accounted for within a multiple memory systems framework.
What is the color of that music performance
- In Proc. Int. Computer Music Conf. (ICMC2005
, 2005
"... The representation of expressivity in music is still a fairly unexplored field. Alternative ways of representing musical information are necessary when providing feedback on emotion expression in music such as in real-time tools for music education, or in the display of large music databases. One po ..."
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Cited by 18 (4 self)
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The representation of expressivity in music is still a fairly unexplored field. Alternative ways of representing musical information are necessary when providing feedback on emotion expression in music such as in real-time tools for music education, or in the display of large music databases. One possible solution could be a graphical non-verbal representation of expressivity in music performance using color as index of emotion. To determine which colors are most suitable for an emotional expression, a test was run. Subjects rated how well each of 8 colors and their 3 nuances corresponds to each of 12 music performances expressing different emotions. Performances were played by professional musicians with 3 instruments, saxophone, guitar, and piano. Results show that subjects associated different hues to different emotions. Also, dark colors were associated to music in minor tonality and light colors to music in major tonality. Correspondence between spectrum energy and color hue are preliminary discussed. 1.
The influence of color on the perception of scene gist
- Journal of Experimental Psychology: Human Perception and Performance
, 2008
"... In 3 experiments the authors used a new contextual bias paradigm to explore how quickly information is extracted from a scene to activate gist, whether color contributes to this activation, and how color contributes, if it does. Participants were shown a brief presentation of a scene followed by the ..."
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Cited by 12 (1 self)
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In 3 experiments the authors used a new contextual bias paradigm to explore how quickly information is extracted from a scene to activate gist, whether color contributes to this activation, and how color contributes, if it does. Participants were shown a brief presentation of a scene followed by the name of a target object. The target object could be consistent or inconsistent with scene gist but was never actually present in the scene. Scene gist activation was operationalized as the degree to which participants respond “yes ” to consistent versus inconsistent objects, reflecting a response bias produced by scene gist. Experiment 1 demonstrated that scene gist is activated after a 42-ms exposure and that the strength of the activation increases with longer presentation durations. Experiments 2 and 3 explored the contribution of color to the activation of scene gist. The results revealed that color has an influence across a wide variety of scenes and is directly associated with scene gist.
Recalibrating color categories using world knowledge
- Psychological Science
, 2008
"... ABSTRACT—When the perceptual system uses color to facilitate object recognition, it must solve the color-constancy problem: The light an object reflects to an observer’s eyes confounds properties of the source of the illumination with the surface reflectance of the object. Information from the visua ..."
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Cited by 12 (2 self)
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ABSTRACT—When the perceptual system uses color to facilitate object recognition, it must solve the color-constancy problem: The light an object reflects to an observer’s eyes confounds properties of the source of the illumination with the surface reflectance of the object. Information from the visual scene (bottom-up information) is insufficient to solve this problem. We show that observers use world knowledge about objects and their prototypical colors as a source of top-down information to improve color constancy. Specifically, observers use world knowledge to recalibrate their color categories. Our results also suggest that similar effects previously observed in language perception are the consequence of a general perceptual process. Observers can use color to identify objects (Brainard, 2004; Oliva & Schyns, 2000; Tanaka, Weiskopf, & Williams, 2001).
Image Retargeting Quality Assessment
, 2011
"... Content-aware image retargeting is a technique that can flexibly display images with different aspect ratios and simultaneously preserve salient regions in images. Recently many image retargeting techniques have been proposed. To compare image quality by different retargeting methods fast and reliab ..."
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Cited by 11 (0 self)
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Content-aware image retargeting is a technique that can flexibly display images with different aspect ratios and simultaneously preserve salient regions in images. Recently many image retargeting techniques have been proposed. To compare image quality by different retargeting methods fast and reliably, an objective metric simulating the human vision system (HVS) is presented in this paper. Different from traditional objective assessment methods that work in bottom-up manner (i.e., assembling pixel-level features in a local-to-global way), in this paper we propose to use a reverse order (top-down manner) that organizes image features from global to local viewpoints, leading to a new objective assessment metric for retargeted images. A scale-space matching method is designed to facilitate extraction of global geometric structures from retargeted images. By traversing the scale space from coarse to fine levels, local pixel correspondence is also established. The objective assessment metric is then based on both global geometric structures and local pixel correspondence. To evaluate color images, CIE L ∗ a ∗ b ∗ color space is utilized. Experimental results are obtained to measure the performance of objective assessments with the proposed metric. The results show good consistency between the proposed objective metric and subjective assessment by human observers.
Object Segmentation By Top-Down Processes
, 2003
"... Introduction We perceive a world organized into familiar objects such as can openers, tractors and picnic tables. Objects are defined by the connectedness of their parts, and we learn about this connectedness through experience [14, 23, 1]. We perceive a can opener as an object because we have noti ..."
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Cited by 10 (3 self)
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Introduction We perceive a world organized into familiar objects such as can openers, tractors and picnic tables. Objects are defined by the connectedness of their parts, and we learn about this connectedness through experience [14, 23, 1]. We perceive a can opener as an object because we have noticed that when we pick up one of its parts, all of the other parts come with it. We perceive a tractor as an object because we have noticed that when one part of the tractor moves, all of the other parts move with it. And, although we may have never seen it move as a whole, we perceive a picnic table as an object because we have noticed that its parts always appear together. While we learn about the connectedness of object parts from visual experience, this connectedness is not always easy to discern in a given visual image [2, 11, 26]. For example, when we look into a kitchen drawer, the parts of the can opener may be contiguous not only with each other but also with parts of the potato ma
Coding of visual object features and feature conjunctions in the human brain. PLoS One
, 2008
"... Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object’s features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles ..."
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Cited by 9 (1 self)
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Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object’s features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process- while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200–400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.
Gender recognition of human faces using color
, 2008
"... ABSTRACT—A continuing question in the object recognition literature is whether surface properties play a role in visual representation and recognition. Here, we examined the use of color as a cue in facial gender recognition by applying a version of reverse correlation to face catego-rization in CIE ..."
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Cited by 8 (2 self)
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ABSTRACT—A continuing question in the object recognition literature is whether surface properties play a role in visual representation and recognition. Here, we examined the use of color as a cue in facial gender recognition by applying a version of reverse correlation to face catego-rization in CIE Lnanbn color space. We found that observ-ers exploited color information to classify ambiguous signals embedded in chromatic noise. The method also allowed us to identify the specific spatial locations and the components of color used by observers. Although the color patterns found with human observers did not accurately mirror objective natural color differences, they suggest sensitivity to the contrast between the main features and the rest of the face. Overall, the results provide evidence that observers encode and can use the local color proper-
Optimality of the Basic Colour Categories for classification
"... Categorization of colour has been widely studied as a window into human language and cognition, and quite separately has been used pragmatically in image-database retrieval systems. This suggests the hypothesis that the best category system for pragmatic purposes coincides with human categories (i.e ..."
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Cited by 6 (0 self)
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Categorization of colour has been widely studied as a window into human language and cognition, and quite separately has been used pragmatically in image-database retrieval systems. This suggests the hypothesis that the best category system for pragmatic purposes coincides with human categories (i.e. the basic colours). We have tested this hypothesis by assessing the performance of different category systems in a machine-vision task. The task was the identification of the odd-one-out from triples of images obtained using a web-based image-search service. In each triple, two of the images had been retrieved using the same search term, the other a different term. The terms were simple concrete nouns. The results were as follows. (1) The odd-one-out task can be performed better than chance using colour alone. (2) Basic colour categorization performs better than random systems of categories. (3) A category system that performs better than the basic colours could not be found. (4) It is not just the general layout of the basic colours that is important, but also the detail. We conclude that (i) the results support the plausibility of an explanation for the basic colours as a result of a pressure-to-optimality, and (ii) the basic colours are good categories for machine vision image-retrieval systems.
Object Recognition in Dense Clutter
"... Observers in recognition experiments invariably view objects against a blank background, while observers of real scenes sometimes view objects against dense clutter. In this study, we examined whether an object’s background affects the information used for recognition. Our stimuli consisted of color ..."
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Cited by 3 (0 self)
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Observers in recognition experiments invariably view objects against a blank background, while observers of real scenes sometimes view objects against dense clutter. In this study, we examined whether an object’s background affects the information used for recognition. Our stimuli consisted of color photographs of everyday objects. The photographs were either organized as a sparse array, as is typical of a visual search experiment, or as high density clutter such as might be found in a toy chest, a handbag or a kitchen drawer. The observer’s task was to locate an animal, vehicle or food target in the stimulus. We varied the information in the stimuli by convolving them with a low pass filter (blur), a high pass filter (edge) or converting them to grayscale. In two experiments, we found that the blur and edge manipulations produced a modest decrement in performance with the sparse arrangement but a severe decrement in performance with the clutter arrangement. These results indicate that the information used for recognition depends on the object’s background. Thus, models of recognition that have been developed for isolated objects may not generalize to objects in dense clutter.
