ALOI

Amsterdam Library of Object Images (ALOI). ALOI is a color image collection of one-thousand small objects, recorded for scientific purposes. In order to capture the sensory variation in object recordings, we systematically varied viewing angle, illumination angle, and illumination color for each object, and additionally captured wide-baseline stereo images. We recorded over a hundred images of each object, yielding a total of 110,250 images for the collection. See Technical Details for a description of the acquisition setup. Details have been published in: J. M. Geusebroek, G. J. Burghouts, and A. W. M. Smeulders, The Amsterdam library of object images, Int. J. Comput. Vision, 61(1), 103-112, January, 2005 (PDF).


References in zbMATH (referenced in 26 articles )

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  1. Barajas-García, Carolina; Solorza-Calderón, Selene; Gutiérrez-López, Everardo: Scale, translation and rotation invariant wavelet local feature descriptor (2019)
  2. Zhao, Henghao; Fu, Liyong; Gao, Zhigang; Ye, Qiaolin; Yang, Zhangjing; Yang, Xubing: Flexible non-greedy discriminant subspace feature extraction (2019)
  3. Le Thi, Hoai An; Le, Hoai Minh; Phan, Duy Nhat; Tran, Bach: Stochastic DCA for sparse multiclass logistic regression (2018)
  4. Mendes Júnior, Pedro R.; de Souza, Roberto M.; de O. Werneck, Rafael; Stein, Bernardo V.; Pazinato, Daniel V.; de Almeida, Waldir R.; Penatti, Otávio A. B.; da S. Torres, Ricardo; Rocha, Anderson: Nearest neighbors distance ratio open-set classifier (2017)
  5. Zhang, Yingjie; Xu, Jianxing; Cheng, H. D.: A novel fuzzy level set approach for image contour detection (2016)
  6. Zimek, Arthur; Vreeken, Jilles: The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives (2015)
  7. Arandjelović, Ognjen: Hallucinating optimal high-dimensional subspaces (2014) ioport
  8. Guimarães Pedronette, Daniel Carlos; Almeida, Jurandy; da S. Torres, Ricardo: A scalable re-ranking method for content-based image retrieval (2014)
  9. Lessmann, Markus; Würtz, Rolf P.: Learning invariant object recognition from temporal correlation in a hierarchical network (2014) ioport
  10. Shao, Zhuhong; Shu, Huazhong; Wu, Jiasong; Chen, Beijing; Coatrieux, Jean Louis: Quaternion Bessel-Fourier moments and their invariant descriptors for object reconstruction and recognition (2014)
  11. Tang, Jun; Shao, Ling; Zhen, Xiantong: Robust point pattern matching based on spectral context (2014) ioport
  12. Campello, R. J. G. B.; Moulavi, D.; Zimek, A.; Sander, J.: A framework for semi-supervised and unsupervised optimal extraction of clusters from hierarchies (2013)
  13. Han, Yuexing: Recognize objects with three kinds of information in landmarks (2013) ioport
  14. Song, Xiaohu; Muselet, Damien; Trémeau, Alain: Affine transforms between image space and color space for invariant local descriptors (2013) ioport
  15. Horta, Danilo; Campello, Ricardo J. G. B.: Automatic aspect discrimination in data clustering (2012)
  16. Shin, Dongjoe; Muller, Jan-Peter: Progressively weighted affine adaptive correlation matching for quasi-dense 3D reconstruction (2012) ioport
  17. Álvarez, Jose M.; Gevers, Theo; López, Antonio M.: Learning photometric invariance for object detection (2010) ioport
  18. Flusser, Jan; Kautsky, Jaroslav; Šroubek, Filip: Implicit moment invariants (2010) ioport
  19. González, Javier; Arévalo, Vicente: Mesh topological optimization for improving piecewise-linear image registration (2010) ioport
  20. Parks, Donovan H.; Levine, Martin D.: Is local colour normalization good enough for local appearance-based classification? (2010) ioport

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