- Region-based image representation
- Semantic representation and processing of image regions
- Object and events detection
- Object class recognition in images and video
- Global scene classification
- Visual context representation and analysis
- Context-driven visual attention
- Semantic annotation of images
Context-based Multimedia Analysis and Representation
Motivation and Objectives
Enhancing the process of image and video classification with semantic characteristics, thus automating the process of semantic segmentation and annotation of multimedia content objects, is a crucial step for narrowing the semantic gap. Combining both low-level descriptors computed automatically from raw multimedia content and semantics in the form of human or automated annotations of audiovisual media and ontologies has been the ultimate task in current multimedia research efforts.
Human vision perception outperforms state-of-the-art computer’s segmentation and recognition algorithms. The main reason for this is that human vision is additionally based on high level a priori knowledge about the semantic meaning of the objects that compose the image. Erroneous image segmentation leads to poor results in recognition of materials and objects, while at the same time, imperfections of global image classification are responsible for deficient segmentation. It is rather obvious that limitations of the former prohibit the efficient operation of the latter and vice versa. Bottom-up automatic annotation and top-down context-based techniques should be combined in a single integrated methodology that handles holistically the gap between semantics and low level visual features.
This special session calls for integrative research papers focusing on the semantic multimedia analysis utilizing contextual knowledge. We are particularly interested in papers that explore interaction between local and global techniques and investigate exploitation of visual context analysis.
Topics
Topics of interest include, but are not limited to:
Organizers and Chairs
- , National Technical University of Athens, Greece
- , National Technical University of Athens, Greece
- , National Technical University of Athens, Greece
Accepted Papers
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Image Classification using an Ant Colony Optimization approach
Tomas Piatrik, Ebroul Izquierdo -
Use of Image Regions in Context-Adaptive Image Classification
Ville Viitaniemi, Jorma Laaksonen -
BPT Enhancement Based on Syntactic and Semantic Criteria
Christian Ferran, Xavier Giro, Ferran Marques, Josep Ramon Casas -
Semantic image analysis using a learning approach and spatial context
Georgios Th. Papadopoulos, Vasileios Mezaris, Stamatia Dasiopoulou, Ioannis Kompatsiaris -
A Context-based Region Labeling Approach for Semantic Image Segmentation
Thanos Athanasiadis, Phivos Mylonas, Yannis Avrithis