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Probabilistic combination of spatial context with visual and co-occurrence information for semantic image analysis
2010
2010 IEEE International Conference on Image Processing
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In this paper, a probabilistic approach to combining spatial context with visual and co-occurrence information for semantic image analysis is presented. ...
and co-occurrence information on the final outcome for every possible pair of semantic concepts. ...
In this paper, a probabilistic approach to combining spatial context with visual and co-occurrence information for semantic image analysis is presented. ...
doi:10.1109/icip.2010.5652615
dblp:conf/icip/PapadopoulosMKS10
fatcat:ttzvwtpg2bgovdmwigy7bbf3jm
A comparative study of object-level spatial context techniques for semantic image analysis
2011
Computer Vision and Image Understanding
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In this paper, three approaches to utilizing object-level spatial contextual information for semantic image analysis are presented and comparatively evaluated. ...
, and the number of supported concepts) on the performance of each spatial context technique, while a detailed analysis of the obtained results is also given. ...
Acknowledgments The work presented in this paper was supported by the European Commission under Contracts FP7-248984 GLOCAL, FP7-214306 JUMAS and FP7-215453 WeKnowIt. ...
doi:10.1016/j.cviu.2011.05.005
fatcat:s63ookmn45hqnpzyscppfwvwly
Visual word disambiguation by semantic contexts
2011
2011 International Conference on Computer Vision
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On the other hand, an image is represented by the occurrence probabilities of semantic contexts. ...
On one hand, for an image, multiple contextspecific bag-of-words histograms are constructed, each of which corresponds to a semantic context. ...
Polysemy of visual words is partly caused by the discard of spatial information. Hence, the use of spatial information can also help to disambiguate visual words. ...
doi:10.1109/iccv.2011.6126257
dblp:conf/iccv/SuJ11
fatcat:ywt7byofkza3hb26g2ny67edve
A Statistical Learning Approach to Spatial Context Exploitation for Semantic Image Analysis
2010
2010 20th International Conference on Pattern Recognition
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In this paper, a statistical learning approach to spatial context exploitation for semantic image analysis is presented. ...
relations after performing an initial classification of image regions to semantic concepts using solely visual information. ...
Among the available contextual information types, spatial context is of increased importance in semantic image analysis. ...
doi:10.1109/icpr.2010.768
dblp:conf/icpr/PapadopoulosMKS10
fatcat:ab3gz55yzjdpxmylkyjfevu4ma
Contextual object categorization with energy-based model
[article]
2016
arXiv
pre-print
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Object categorization is a hot issue of an image mining. Contextual information between objects is one of the important semantic knowledge of an image. ...
Then, the spatial relations were considered as well as co-occurrence and appearance of objects by using energy-based model, where the energy function was defined as the region-object association potential ...
with co-occurrence and spatial constraints of objects in an image. ...
arXiv:1604.06852v1
fatcat:32vsvfwqcjgstnar7iat4stqaq
Context based object categorization: A critical survey
2010
Computer Vision and Image Understanding
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Several models for object categorization use appearance and context information from objects to improve recognition accuracy. ...
The goal of object categorization is to locate and identify instances of an object category within an image. ...
The majority of the context-based models include at most two different types of context, semantic and spatial, since the complexity to determine scale context is still high for 2D images. ...
doi:10.1016/j.cviu.2010.02.004
fatcat:3ee2st4tffbnplewyrq5o4i5rm
Visual pattern discovery in image and video data: a brief survey
2013
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
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In image and video data, visual pattern refers to re-occurring composition of visual primitives. Such visual patterns extract the essence of the image and video data that convey rich information. ...
However, unlike frequent patterns in transaction data, there are considerable visual content variations and complex spatial structures among visual primitives, which make effective exploration of visual ...
. 38, 60
Classic Topic Model for Visual Pattern Discovery The topic model, such as LDA 15 and probabilistic latent semantic analysis (pLSA), 92 discovers semantic topics from a corpus of documents ...
doi:10.1002/widm.1110
fatcat:skjnmv5njfdtxc3erl4r2txqri
Context-aware image semantic extraction in the social web
2012
Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion
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With the advent of the paradigm of Web 2.0 especially the past five years, the concept of image context has further evolved, allowing users to tag their own and other people's pictures. ...
Focusing on tagging, we distinguish between static and dynamic features. The set of static features include textual and visual features, as well as the contextual information. ...
Tour Eiffel) and visual description (sunset, sky). For this purpose the features used to mine the dataset was time, location, visual information and tags co-occurrence. ...
doi:10.1145/2187980.2188005
dblp:conf/www/Ruocco12
fatcat:lmd63pxt6zfy3igcghgsnsyc54
Context modeling in computer vision: techniques, implications, and applications
2010
Multimedia tools and applications
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This review is intended to introduce researchers in computer vision and image analysis to this increasingly important field as well as provide a reference for those who may wish to incorporate context ...
In recent years there has been a surge of interest in context modeling for numerous applications in computer vision. ...
Acknowledgements The authors would like to thank Geraldine Morin, Pierre Gurdjos, Viorica Patraucean, and Jerôme Guenard, for the insightful discussions and constructive suggestions. ...
doi:10.1007/s11042-010-0631-y
fatcat:cspmqzbtinexrghz2zxjklkyva
Semantic segmentation of street scenes by superpixel co-occurrence and 3D geometry
2009
2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops
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The main novelty of this generative approach is the introduction of an explicit model of spatial co-occurrence of visual words associated with super-pixels and utilization of appearance, geometry and contextual ...
We present a novel approach for image semantic segmentation of street scenes into coherent regions, while simultaneously categorizing each region as one of the predefined categories representing commonly ...
The semantic segmentation of the street view scenes requires special attention because of their practical importance, difficulty, and impossibility of standard techniques to score equally well as on standard ...
doi:10.1109/iccvw.2009.5457645
dblp:conf/iccvw/MicuslikK09
fatcat:2m2g6ox4unfazlpgl5rdubmrya
Spatially Constrained Location Prior for scene parsing
2016
2016 International Joint Conference on Neural Networks (IJCNN)
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2018 pre-print arXiv:1802.08790v1 fatcat:63vdkrumybcqzggfy2gjl6tkjm
Semantic context is an important and useful cue for scene parsing in complicated natural images with a substantial amount of variations in objects and the environment. ...
This paper proposes Spatially Constrained Location Prior (SCLP) for effective modelling of global and local semantic context in the scene in terms of inter-class spatial relationships. ...
ACKNOWLEDGMENT This research was supported under Australian Research Council's Linkage and Discovery Projects funding scheme (project numbers LP140100939 and DP160102639). ...
doi:10.1109/ijcnn.2016.7727373
dblp:conf/ijcnn/ZhangVSC16
fatcat:ygw4gvgcqvhobbjxnczt5ipwjq
Geographic Scene Understanding of High-Spatial-Resolution Remote Sensing Images: Methodological Trends and Current Challenges
2022
Applied Sciences
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It has become a research hotspot to recognize the semantic information of objects, analyze the semantic relationship between objects and then understand the more abstract geographic scenes in high-spatial-resolution ...
Then, the achievements in the processing strategies and techniques of geographic scene understanding in recent years are reviewed from three layers: visual semantics, object semantics and concept semantics ...
Acknowledgments: The authors thank Xueying Zhang and Chunju Zhang for their critical reviews and constructive comments.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app12126000
fatcat:hgtv363m6ras5me5vnu7d6yeii
Semantic Concept Co-Occurrence Patterns for Image Annotation and Retrieval
2016
IEEE Transactions on Pattern Analysis and Machine Intelligence
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ACKNOWLEDGMENTS This material is based upon work supported by the National Science Foundation under Grant No. 0905671 and 1552454. ...
The reason for this is that the combined measure can leverage both the global and local co-occurrences as well as utilize both the semantic and visual information. ...
for building individual concept inference models and the utilization of co-occurrence patterns for refinement of concept signature as a way to encode both visual and semantic information. ...
doi:10.1109/tpami.2015.2469281
pmid:26959678
fatcat:enu2lsrmzfgsfp4vvf5hj3d27y
An Evidence-Driven Probabilistic Inference Framework for Semantic Image Understanding
[chapter]
2009
Lecture Notes in Computer Science
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This work presents an image analysis framework driven by emerging evidence and constrained by the semantics expressed in an ontology. ...
Experiments conducted for two different image analysis tasks showed improvement in performance, compared to the case where computer vision techniques act isolated from any type of knowledge or context. ...
This work was funded by the X-Media project (www.xmedia-project.org) sponsored by the European Commission as part of the Information Society Technologies (IST) programme under EC grant number IST-FP6-026978 ...
doi:10.1007/978-3-642-03070-3_40
fatcat:vryt24d42rdwvoz5ady7qgekue
Context Based Visual Content Verification
[article]
2017
arXiv
pre-print
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In this paper the intermediary visual content verification method based on multi-level co-occurrences is studied. ...
We show that the usage of context greatly improve the accuracy of verification with up to 16% improvement. ...
and spatial co-occurrences. ...
arXiv:1709.00141v1
fatcat:36ci4caixnf2jgafzvxij3byne
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