Spatial Context - Images

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Spatial Context - Images
Domain Outdoor images
Media Image
Size 127 MB
Instances 923 images
File Format JPEG
Creation Date 2009
Task Concept detection
Copyright The dataset is publicly available for non-commercial use.
URL http://mklab.iti.gr/project/scef


Description

The dataset includes: a) the utilized image set, b) the image segmentation masks, c) region-level manual image annotation, d) the extracted low-level features, e) the computed fuzzy directional spatial relations, and f) the region classification results based solely on visual information.

Quality

JPG compressed images.

Source

The image set was provided by Alinari 24 ORE (http://www.alinari.com, info: euproject-2@alinari.it).

Ground Truth Annotation

Concept annotations

Includes the region-level manual image annotations, which were used for training and evaluation. Supported concepts: Building, Foliage, Mountain, Person, Road, Sailing-boat, Sand, Sea, Sky, Snow.

Directional Relations

Includes the fuzzy directional spatial relations computed for every image. Supported spatial relations: Above (A), Above-Right (AR), Above-Left (AL), Right (R), Left (L), Below (B), Below-Right (BR), Below-Left (BL). Each spatial relation is estimated for every possible image region pair and receives values in the interval []1,0. ‘Ground’ region denotes the image region used as reference, while ‘Figure’ region is the region whose relative position is estimated with respect to the ‘ground’ region.

Features

Segmentation masks

Includes the segmentation mask for every image. This is stored as grey scaled image (binary pgm format), where the intensity value at each pixel denotes the image region to which the particular pixel belongs. Pixel intensity receives values in the interval [0, N-1] where N is the number of regions to which every image is segmented. In order to better visualize the segmentation masks use a .pgm image viewer and perform histogram equalization

Visual features

The low-level features extracted for every image segment. Two sets of features are available: a) MPEG-7 descriptors: Homogeneous Texture, Scalable Color, Edge Histogram and Region Shape, b) wavelet-based features.

Classification results

The region-level classification results for the following feature-classifier combinations: MPEG-7-SVM, MPEG-7-ML, Wavelet-ML. A degree of confidence is estimated for every possible region-concept pair.

Copyright Remarks

The dataset is publicly available for non-commercial use.

Citation

Please refer to [Papadopoulos et al., Proc. WIAMIS'09, London, UK] if this dataset is used for experimentation in publications.

External Links

http://mklab.iti.gr/project/scef

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