LabelMe: A Database and Web-Based Tool for Image Annotation

Russell, Bryan; Torralba, Antonio; Murphy, Kevin; Freeman, William T.

doi:10.1007/s11263-007-0090-8

Cited by 3,038 publications

(1,428 citation statements)

References 34 publications

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“…Stimuli presented in the search trials (75 % of trials) were 480 color photographs of real-world scenes obtained from the LabelMe online database (Russell, Torralba, Murphy, & Freeman, 2008;see Fig. 1b for some examples) and were divided into scenes containing cars (n = 240), people (n = 240), both cars and people (n = 240), or neither cars nor people (n = 240).…”

Section: Natural Scene Stimulimentioning

confidence: 99%

Involuntary attentional capture by task-irrelevant objects that match the search template for category detection in natural scenes

Reeder

Zoest

Peelen

2015

Atten Percept Psychophys

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Theories of visual search postulate that the selection of targets amongst distractors involves matching visual input to a top-down attentional template. Previous work has provided evidence that feature-based attentional templates affect visual processing globally across the visual field. In the present study, we asked whether more naturalistic, categorylevel attentional templates also modulate visual processing in a spatially global and obligatory way. Subjects were cued to detect people or cars in a diverse set of photographs of realworld scenes. On a subset of trials, silhouettes of people and cars appeared in search-irrelevant locations that subjects were instructed to ignore, and subjects were required to respond to the location of a subsequent dot probe. In three experiments, results showed a consistency effect on dot-probe trials: dot probes were detected faster when they appeared in the location of the cued category compared with the non-cued category, indicating attentional capture by template-matching stimuli. Experiments 1 and 2 showed that this capture was involuntary: consistency effects persisted under conditions in which attending to silhouettes of the cued category was detrimental to performance. Experiment 3 tested whether these effects could be attributed to non-attentional effects related to the processing of the category cues. Results showed a consistency effect when subjects searched for category exemplars but not when they searched for objects semantically related to the cued category. Together, these results indicate that attentional templates for familiar object categories affect visual processing across the visual field, leading to involuntary attentional capture by template-matching stimuli.

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Section: Natural Scene Stimulimentioning

confidence: 99%

Involuntary attentional capture by task-irrelevant objects that match the search template for category detection in natural scenes

Reeder

Zoest

Peelen

2015

Atten Percept Psychophys

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“…3.2 is another dataset named "lu_wei_feb_2006" was also used in order to have different type of images and ultimately study the efficiency geodesic active contour approach. This dataset was prepared by Russell et al (2008) from Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, USA. Unfortunately, there is no detail information regarding the equipment used or standard operating procedure (S.O.P) on how the images were acquired (Russell et al, 2008).…”

Section: Methodsmentioning

confidence: 99%

Implementation of Geodesic Active Contour Approach for Pigment Spots Segmentation on the Iris Surface

Man

Jabal

Rahim

et al. 2016

Journal of Computer Science

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Abstract:The aim of this paper is to study the effectiveness of geodesic active contour approach to segment the pigment spots on iris surface. Pigment spot is an abnormal marker that appears on the iris surface, which may lead to eye diseases. The multi appearance, scattered location and dynamic shape of the pigment spots on the iris surface make them very difficult to detect using automatic segmentation method. Therefore, this paper presents the preliminary works that observe the efficiency and accuracy of geodesic active contour approach to automatically segment the pigment spots on iris surface. Miles database and "lu_wei_feb_2006" dataset are used in this study. The results of the conducted experiment show that geodesic active contour approach able to correctly and accurately detect up to 77% and 90% of the pigment spots in Miles database and "lu_wei_feb_2006" dataset, respectively.

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“…This process is also known as image annotation and it is useful for information retrieval (Mocanu, 2010;Paul & Beegom, 2010;Russell et al, 2008). ImageStore is the database application where information is saved after images processing.…”

Section: Data Storage Modulementioning

confidence: 99%

Geographic Image Mining

Boicea¹,

Rădulescu²,

Truică³

et al. 2016

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ABSTRACT:Image segmentation is a branch of the image processing domain which involves partitioning the image into multiple segments referred to as sets of pixels. The segmentation purpose is to change the representation of an image into a form that is analyzed easier and less processed in order to extract information based on the colors in the image. This paper shows how we can determine statistics on the relief by processing the images that represent geographic maps through Data Mining algorithms. The important aspects of this type of mining are also described in this study. A dedicated application is used for data processing.

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LabelMe: A Database and Web-Based Tool for Image Annotation

Cited by 3,038 publications

References 34 publications

Involuntary attentional capture by task-irrelevant objects that match the search template for category detection in natural scenes

Involuntary attentional capture by task-irrelevant objects that match the search template for category detection in natural scenes

Implementation of Geodesic Active Contour Approach for Pigment Spots Segmentation on the Iris Surface

Geographic Image Mining

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