Alignment of uncalibrated images for multi-view classification
Proceedings - International Conference on Image Processing, ICIP
2365 - 2368
MetadataShow full item record
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/28279
Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pair-wise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of images is necessary prior to distance computation. We propose a method for the registration of uncalibrated images that capture the same 3D scene or object. We model the depth map of the scene as an algebraic surface, which yields a warp model in the form of a rational function between image pairs. The warp model is computed by minimizing the registration error, where the registered image is a weighted combination of two images generated with two different warp functions estimated from feature matches and image intensity functions in order to provide robust registration. We demonstrate the flexibility of our alignment method by experimentation on several wide-baseline image pairs with arbitrary scene geometries and texture levels. Moreover, the results on multi-view image classification suggest that the proposed alignment method can be effectively used in graph-based classification algorithms for the computation of pairwise distances where it achieves significant improvements over distance computation without prior alignment. © 2011 IEEE.
- Conference Paper 2294
Showing items related by title, author, creator and subject.
Self-aligned and bundled electrospun fibers prepared from blends of polystyrene (PS) and poly(methyl methacrylate) (PMMA) with a hairy-rod polyphenylene copolymer Uyar, T.; Cianga I.; Cianga L.; Besenbacher F.; Yagci, Y. (2009)Bundled and self-aligned fibers were obtained by electrospinning blends of polystyrene (PS) and poly(methyl methacrylate) (PMMA) with a hairy-rod polyphenylene-g-polystyrene/poly(a-caprolactone) (PP-g-PS/PCL) copolymer. ...
Detection of compound structures using hierarchical clustering of statistical and structural features Akçay H.G.; Aksoy, S. (2011)We describe a new procedure that combines statistical and structural characteristics of simple primitive objects to discover compound structures in images. The statistical information that is modeled using spectral, shape, ...
Machine-based learning system: Classification of ADHD and non-ADHD participants [Makina temelli öǧrenim sistemi: DEHB olan ve olmayan katilimcilarin siniflandirmasi] Oztoprak H.; Toycan M.; Alp Y.K.; Arikan O.; Dogutepe E.; Karakas S. (Institute of Electrical and Electronics Engineers Inc., 2017)Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is ...