Download An Introduction to Object Recognition: Selected Algorithms by Marco Alexander Treiber PDF

By Marco Alexander Treiber

ISBN-10: 1849962340

ISBN-13: 9781849962346

Rapid improvement of laptop has enabled utilization of automated item popularity in progressively more purposes, starting from business photograph processing to clinical purposes, in addition to projects brought on through the common use of the net. each one zone of program has its particular requisites, and for that reason those can't all be tackled adequately via a unmarried, general-purpose set of rules.

This easy-to-read text/reference presents a finished creation to the sector of item popularity (OR). The ebook offers an outline of the various functions for OR and highlights vital set of rules periods, featuring consultant instance algorithms for every category. The presentation of every set of rules describes the fundamental set of rules move intimately, entire with graphical illustrations. Pseudocode implementations also are integrated for lots of of the tools, and definitions are provided for phrases that may be unusual to the amateur reader. assisting a transparent and intuitive instructional variety, using arithmetic is saved to a minimum.

Topics and features:

  • Presents instance algorithms overlaying international methods, transformation-search-based equipment, geometrical version pushed equipment, 3D item acceptance schemes, versatile contour becoming algorithms, and descriptor-based methods
  • Explores each one approach in its entirety, instead of targeting person steps in isolation, with an in depth description of the circulate of every set of rules, together with graphical illustrations
  • Explains the real ideas at size in a simple-to-understand variety, with a minimal utilization of mathematics
  • Discusses a huge spectrum of functions, together with a few examples from advertisement products
  • Contains appendices discussing subject matters concerning OR and conventional within the algorithms, (but no longer on the middle of the tools defined within the chapters)

Practitioners of business photograph processing will locate this easy creation and assessment to OR a useful reference, as will graduate scholars in laptop imaginative and prescient courses.

Marco Treiber is a software program developer at ASM meeting structures, Munich, Germany, the place he's Technical Lead in photograph Processing for the imaginative and prescient approach of SiPlace placement machines, utilized in SMT assembly.

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Additional resources for An Introduction to Object Recognition: Selected Algorithms for a Wide Variety of Applications

Sample text

For many applications, especially if arbitrarily shaped objects are to be recognized, it is most convenient if the algorithm automatically learns the range of expected appearance variations. This is done in a training stage prior to recognition. A simple strategy would be to sample the object at different poses, different illumination settings and perhaps also from different viewpoints, and store all training images in the model. However, this is inefficient as the training images all show the same object and despite the variances almost certainly exhibit a considerable amount of redundancy.

They point out that it is desirable to maximize the inter-class variance by the transformation, whereas intra-class variance is to be minimized at the same time. As a result, the transformed training samples should build compact clusters located far from each other in transformed space. 22) with SB denoting the between-class scattermatrix and SC the within-class scattermatrix. References 1. J, 1982, ISBN 0-131-65316-4 2. , Hespanha, J. and Kriegman, D. “Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):711–720, 1997 3.

The compact representation allows a fast comparison of objects, which makes the method applicable in online retrieval applications. Despite still being a global scheme, the method can also cope with occlusion to some extent. However, a proper segmentation from the background is still necessary. 1 Main Idea The principal component analysis (PCA) aims at transforming the gray value object appearance into a more advantageous representation. According to Murase and Nayar [10], the appearance of an object in an image depends on the object shape, its reflectance properties, the object pose, and the illumination conditions.

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