Authors:
Mouna Dammak
;
Mahmoud Mejdoub
and
Chokri Ben Amar
Affiliation:
National Engineering School of Sfax and University of Sfax, Tunisia
Keyword(s):
Image Representation, Spatial Neighboring Relation, Bag of Visual Words, Encoding and Pooling, Graph Representation, Image Categorization.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
Abstract:
The semantic gap is a crucial issue in the enhancement of computer vision. The user longs for retrieving images on a semantic level, but the image characterizations can only give a low-level similarity. As a result, recording a stage medium between high-level semantic concepts and low-level visual features is a stimulating task. A recent work, called Bag of visual Words (BoW) have arisen to resolve this difficulty in greater generality through the conception of techniques genius relevantly learning semantic vocabularies. In spite of its clarity and effectiveness, the building of a codebook is a critical step which is ordinarily performed by coding and pooling step. Yet, it is still difficult to build a compact codebook with shortened calculation cost. For that, several approaches try to overcome these difficulties and to improve image representation. In this paper, we introduce a survey investigates to cover the inadequacy of a full description of the most important public approaches
for image categorization and retrieval.
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