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Probabilistic combination of spatial context with visual and co-occurrence information for semantic image analysis

Georgios Th. Papadopoulos, Vasileios Mezaris, Ioannis Kompatsiaris, Michael G. Strintzis
2010 2010 IEEE International Conference on Image Processing  
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

G.Th. Papadopoulos, C. Saathoff, H.J. Escalante, V. Mezaris, I. Kompatsiaris, M.G. Strintzis
2011 Computer Vision and Image Understanding  
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

Yu Su, Frederic Jurie
2011 2011 International Conference on Computer Vision  
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

Georgios Th. Papadopoulos, Vasileios Mezaris, Ioannis Kompatsiaris, Michael G. Strintzis
2010 2010 20th International Conference on Pattern Recognition  
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]

Changyong Ri, Duho Pak, Cholryong Choe, Suhyang Kim, Yonghak Sin
2016 arXiv   pre-print
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

Carolina Galleguillos, Serge Belongie
2010 Computer Vision and Image Understanding  
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

Hongxing Wang, Gangqiang Zhao, Junsong Yuan
2013 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery  
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

Massimiliano Ruocco
2012 Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion  
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

Oge Marques, Elan Barenholtz, Vincent Charvillat
2010 Multimedia tools and applications  
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

Branislav Micusik, Jana Kosecka
2009 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops  
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

Ligang Zhang, Brijesh Verma, David Stockwell, Sujan Chowdhury
2016 2016 International Joint Conference on Neural Networks (IJCNN)  
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

Peng Ye, Guowei Liu, Yi Huang
2022 Applied Sciences  
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

Linan Feng, Bir Bhanu
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence  
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]

Spiros Nikolopoulos, Georgios Th. Papadopoulos, Ioannis Kompatsiaris, Ioannis Patras
2009 Lecture Notes in Computer Science  
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]

Martin Lukac, Aigerim Bazarbayeva, Michitaka Kameyama
2017 arXiv   pre-print
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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