Stereoscopic Depth: Its Relation to Image Segmentation, Grouping, and the Recognition of Occluded Objects

Perception ◽  
1989 ◽  
Vol 18 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Ken Nakayama ◽  
Shinsuke Shimojo ◽  
Gerald H Silverman
Keyword(s):  
Image Segmentation ◽  
Object Recognition ◽  
Visual Processing ◽  
Template Matching ◽  
Stereoscopic Depth ◽  
Spatial Relationships ◽  
Object Shape ◽  
Occluded Objects ◽  
Surface Description ◽  
The Common

Image regions corresponding to partially hidden objects are enclosed by two types of bounding contour: those inherent to the object itself (intrinsic) and those defined by occlusion (extrinsic). Intrinsic contours provide useful information regarding object shape, whereas extrinsic contours vary arbitrarily depending on accidental spatial relationships in scenes. Because extrinsic contours can only degrade the process of surface description and object recognition, it is argued that they must be removed prior to a stage of template matching. This implies that the two types of contour must be distinguished relatively early in visual processing and we hypothesize that the encoding of depth is critical for this task. The common border is attached to and regarded as intrinsic to the closer region, and detached from and regarded as extrinsic to the farther region. We also suggest that intrinsic borders aid in the segmentation of image regions and thus prevent grouping, whereas extrinsic borders provide a linkage to other extrinsic borders and facilitate grouping. Support for these views is found in a series of demonstrations, and also in an experiment where the expected superiority of recognition was found when partially sampled faces were seen in a back rather than a front stereoscopic depth plane.

Featural and Configural Processing of Faces and Houses in Matched Dyslexic and Typical Readers

2020 ◽  
Author(s):  
Bahareh Jozranjbar ◽  
Arni Kristjansson ◽  
Heida Maria Sigurdardottir
Keyword(s):  
Object Recognition ◽  
Visual Processing ◽  
Reading Ability ◽  
Visual Recognition ◽  
Reading Deficits ◽  
Domain Specific ◽  
Configural Information ◽  
Lower House ◽  
Single Process ◽  
Processing Mechanisms

While dyslexia is typically described as a phonological deficit, recent evidence suggests that ventral stream regions, important for visual categorization and object recognition, are hypoactive in dyslexic readers who might accordingly show visual recognition deficits. By manipulating featural and configural information of faces and houses, we investigated whether dyslexic readers are disadvantaged at recognizing certain object classes or utilizing particular visual processing mechanisms. Dyslexic readers found it harder to recognize objects (houses), suggesting that visual problems in dyslexia are not completely domain-specific. Mean accuracy for faces was equivalent in the two groups, compatible with domain-specificity in face processing. While face recognition abilities correlated with reading ability, lower house accuracy was nonetheless related to reading difficulties even when accuracy for faces was kept constant, suggesting a specific relationship between visual word recognition and the recognition of non-face objects. Representational similarity analyses (RSA) revealed that featural and configural processes were clearly separable in typical readers, while dyslexic readers appeared to rely on a single process. This occurred for both faces and houses and was not restricted to particular visual categories. We speculate that reading deficits in some dyslexic readers reflect their reliance on a single process for object recognition.

Multiband Image Segmentation and Object Recognition for Understanding Road Scenes

2011 ◽  
Vol 12 (4) ◽  
pp. 1423-1433 ◽  
Author(s):  
Yousun Kang ◽  
Koichiro Yamaguchi ◽  
Takashi Naito ◽  
Yoshiki Ninomiya
Keyword(s):  
Image Segmentation ◽  
Object Recognition

scholarly journals Fast Algorithm for Selective Image Segmentation Model

2018 ◽  
Vol 7 (4.33) ◽  
pp. 41
Author(s):  
Abdul K Jumaat ◽  
Ke Chen
Keyword(s):  
Image Segmentation ◽  
Fast Algorithm ◽  
Visual Quality ◽  
Projection Algorithm ◽  
Computational Time ◽  
Segmentation Result ◽  
Numerical Tests ◽  
Specific Object ◽  
The Common

Selective image segmentation model aims to separate a specific object from its surroundings. To solve the model, the common practice to deal with its non-differentiable term is to approximate the original functional. While this approach yields to successful segmentation result, however the segmentation process can be slow. In this paper, we showed how to solve the model without approximation using Chambolle’s projection algorithm. Numerical tests show that good visual quality of segmentation is obtained in a fast-computational time.  

scholarly journals The representation of colored objects in macaque color patches

2017 ◽  
Author(s):  
Le Chang ◽  
Pinglei Bao ◽  
Doris Y. Tsao
Keyword(s):  
Object Recognition ◽  
Color Vision ◽  
The Other ◽  
Color Patch ◽  
Shape Information ◽  
Object Shape ◽  
Shape Invariant ◽  
High Concentrations ◽  
The Brain

AbstractAn important question about color vision is: how does the brain represent the color of an object? The recent discovery of “color patches” in macaque inferotemporal (IT) cortex, the part of brain responsible for object recognition, makes this problem experimentally tractable. Here we record neurons in three color patches, middle color patch CLC (central lateral color patch), and two anterior color patches ALC (anterior lateral color patch) and AMC (anterior medial color patch), while presenting images of objects systematically varied in hue. We found that all three patches contain high concentrations of hue-selective cells, and the three patches use distinct computational strategies to represent colored objects: while all three patches multiplex hue and shape information, shape-invariant hue information is much stronger in anterior color patches ALC/AMC than CLC; furthermore, hue and object shape specifically for primate faces/bodies are over-represented in AMC but not in the other two patches.

A Study on Retinal Image Segmentation and Registration Methods

2021 ◽  
pp. 25-33
Author(s):  
B. Sivaranjani ◽  
C. Kalaiselvi
Keyword(s):  
Image Segmentation ◽  
Retinal Image ◽  
Template Matching ◽  
Diagnosis And Treatment ◽  
Retinal Images ◽  
Fundus Images ◽  
Image Preprocessing ◽  
Fundus Camera ◽  
Motion Parameters ◽  
Retinal Image Segmentation

Diagnosis and treatment of several disorders affecting the retina and the choroid behind it require capturing a sequence of fundus images using the fundus camera. These images are to be processed for better diagnosis and planning of treatment. Retinal image template matching is greatly required to extract certain features that may help in diagnosis and treatment. Also registration of retinal images is very useful in extracting the motion parameters that help in composing a complete map for the retina as well as in retinal tracking. This paper introduces a survey for the image preprocessing, dimensionality reduction, template matching and registration techniques that were reported as being well for retinal images.

Logical atomism

2018 ◽  
Author(s):  
Alex Oliver
Keyword(s):  
Mutual Influence ◽  
Ordinary Language ◽  
Common Theme ◽  
Complex Sentences ◽  
Logical Atomism ◽  
The First World War ◽  
The World ◽  
Surface Description ◽  
The Common ◽  
First World

The name ‘logical atomism’ refers to a network of theses about the parts and structure of the world and the means by which language represents the world. Wittgenstein, in his Tractatus Logico-Philosophicus, expounds a version of logical atomism developed by him around the time of the First World War, as does Russell in works published contemporaneously. It is no accident that their work on logical atomism shares a common surface description since it resulted from their mutual influence at Cambridge. The common theme is that the meaning of our sentences is rooted in a primitive relation between simple expressions and their simple worldly bearers, the logical atoms. In a logically perfect language, atomic sentences describe configurations of these atoms, and complex sentences are combinations of the atomic sentences. But sentences of ordinary language may have a misleading surface form which is revealed as such by analysis. The common theme masks considerable differences of doctrine. In particular, there are differences in the nature of logical atoms and in the arguments for the existence of these atoms.

Visual word recognition models should also be constrained by knowledge about the visual system

2012 ◽  
Vol 35 (5) ◽  
pp. 287-287 ◽  
Author(s):  
Pablo Gomez ◽  
Sarah Silins
Keyword(s):  
Object Recognition ◽  
Word Recognition ◽  
Visual System ◽  
Visual Word Recognition ◽  
Visual Processing ◽  
Visual Word ◽  
Universal Models ◽  
European Languages ◽  
Models Of Reading ◽  
Reading Models

AbstractFrost's article advocates for universal models of reading and critiques recent models that concentrate in what has been described as “cracking the orthographic code.” Although the challenge to develop models that can account for word recognition beyond Indo-European languages is welcomed, we argue that reading models should also be constrained by general principles of visual processing and object recognition.

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