On a Quest for Image Descriptors Based on Unsupervised Segmentation Maps
- 1 August 2010
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 10514651,p. 762-765
- https://doi.org/10.1109/icpr.2010.192
Abstract
This paper investigates segmentation-based image descriptors for object category recognition. In contrast to commonly used interest points the proposed descriptors are extracted from pairs of adjacent regions given by a segmentation method. In this way we exploit semi-local structural information from the image. We propose to use the segments as spatial bins for descriptors of various image statistics based on gradient, colour and region shape. Proposed descriptors are validated on standard recognition benchmarks. Results show they outperform state-of-the-art reference descriptors with 5.6x less data and achieve comparable results to them with 8.6x less data. The proposed descriptors are complementary to SIFT and achieve state-of-the-art results when combined together within a kernel based classifier.Keywords
This publication has 12 references indexed in Scilit:
- Visual category recognition using Spectral Regression and Kernel Discriminant AnalysisPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Visual Word AmbiguityPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Segmentation Based Interest Points and Evaluation of Unsupervised Image Segmentation MethodsPublished by British Machine Vision Association and Society for Pattern Recognition ,2009
- A comparison of color features for visual concept classificationPublished by Association for Computing Machinery (ACM) ,2008
- A fast local descriptor for dense matchingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2008
- Learning Local Image DescriptorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- A Comparison of Affine Region DetectorsInternational Journal of Computer Vision, 2005
- A performance evaluation of local descriptorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- The pyramid match kernel: discriminative classification with sets of image featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Object recognition from local scale-invariant featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999