An introduction to genetic algorithms
An introduction to genetic algorithms
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automating the linking of content and concept
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Support Vector Machines for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Old Fashioned State-of-the-Art Image Classification
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Handbook on Ontologies (International Handbooks on Information Systems)
Handbook on Ontologies (International Handbooks on Information Systems)
Generating fuzzy semantic metadata describing spatial relations from images using the R-histogram
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
Retrieval Method for Multi-category Images
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Ontology Based Object Learning and Recognition: Application to Image Retrieval
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Evaluating the application of semantic inferencing rules to image annotation
Proceedings of the 3rd international conference on Knowledge capture
Computing and Managing Cardinal Direction Relations
IEEE Transactions on Knowledge and Data Engineering
Applying multi-class SVMs into scene image classification
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Image Classification and Retrieval using Correlation
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
A New Method for Image Classification by Using Multilevel Association Rules
ICDEW '05 Proceedings of the 21st International Conference on Data Engineering Workshops
A learning approach to semantic image analysis
MobiMedia '06 Proceedings of the 2nd international conference on Mobile multimedia communications
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Fusing MPEG-7 visual descriptors for image classification
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Semantic annotation of images and videos for multimedia analysis
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
Knowledge-assisted semantic video object detection
IEEE Transactions on Circuits and Systems for Video Technology
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
Integrating Image Segmentation and Classification for Fuzzy Knowledge-Based Multimedia Indexing
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Combining image captions and visual analysis for image concept classification
Proceedings of the 9th International Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD 2008
An Evidence-Driven Probabilistic Inference Framework for Semantic Image Understanding
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
A system for the semantic multimodal analysis of news audio-visual content
EURASIP Journal on Advances in Signal Processing
An energy-based model for region-labeling
Computer Vision and Image Understanding
Visual graph modeling for scene recognition and mobile robot localization
Multimedia Tools and Applications
Image interpretation by combining ontologies and bayesian networks
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
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A learning approach to knowledge-assisted image analysis and classification is proposed that combines global and local information with explicitly defined knowledge in the form of an ontology. The ontology specifies the domain of interest, its subdomains, the concepts related to each subdomain as well as contextual information. Support vector machines (SVMs) are employed in order to provide image classification to the ontology subdomains based on global image descriptions. In parallel, a segmentation algorithm is applied to segment the image into regions and SVMs are again employed, this time for performing an initial mapping between region low-level visual features and the concepts in the ontology. Then, a decision function, that receives as input the computed region-concept associations together with contextual information in the form of concept frequency of appearance, realizes image classification based on local information. A fusion mechanism subsequently combines the intermediate classification results, provided by the local-and global-level information processing, to decide on the final image classification. Once the image subdomain is selected, final region-concept association is performed using again SVMs and a genetic algorithm (GA) for optimizing the mapping between the image regions and the selected subdomain concepts taking into account contextual information in the form of spatial relations. Application of the proposed approach to images of the selected domain results in their classification (i.e., their assignment to one of the defined subdomains) and the generation of a fine granularity semantic representation of them (i.e., a segmentation map with semantic concepts attached to each segment). Experiments with images from the personal collection domain, as well as comparative evaluation with other approaches of the literature, demonstrate the performance of the proposed approach.