iccv iccv2013 iccv2013-447 iccv2013-447-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Jonathan T. Barron, Mark D. Biggin, Pablo Arbeláez, David W. Knowles, Soile V.E. Keranen, Jitendra Malik
Abstract: We present an algorithm for the per-voxel semantic segmentation of a three-dimensional volume. At the core of our algorithm is a novel “pyramid context” feature, a descriptive representation designed such that exact per-voxel linear classification can be made extremely efficient. This feature not only allows for efficient semantic segmentation but enables other aspects of our algorithm, such as novel learned features and a stacked architecture that can reason about self-consistency. We demonstrate our technique on 3Dfluorescence microscopy data ofDrosophila embryosfor which we are able to produce extremely accurate semantic segmentations in a matter of minutes, and for which other algorithms fail due to the size and high-dimensionality of the data, or due to the difficulty of the task.
[1] B. Andres, T. Kroeger, K. Briggman, W. Denk, N. Korogod, G. Knott, U. Koethe, and F. Hamprecht. Globally optimal closed-surface segmentation for connectomics. ECCV, 2012.
[2] P. Arbel ´aez, B. Hariharan, C. Gu, S. Gupta, L. Bourdev, and J. Malik. Semantic segmentation using regions and parts. CVPR, 2012.
[3] S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. TPAMI, 2002.
[4] A. C. Berg, T. L. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondences. CVPR, 2005.
[5] A. C. Berg and J. Malik. Geometric blur for template matching. CVPR, 2001.
[6] X. Boix, J. Gonfaus, J. van de Weijer, A. Bagdanov, J. Serrat, and J. Gonzalez. Harmony potentials: Fusing global and local scale for semantic image segmentation. IJCV, 2012.
[7] J. Campos-Ortega and V. Hartenstein. The embryonic development of drosophila melanogaster. Springer, 1997.
[8] J. Carreira, R. Caseiro, J. Batista, and C. Sminchisescu. Semantic segmentation with second-order pooling. ECCV, 2012.
[9] J. Carreira, F. Li, and C. Sminchisescu. Object recognition by sequential figure-ground ranking. IJCV, 2012.
[10] J. Chen, S. Paris, and F. Durand. Real-time edge-aware image processing with the bilateral grid. SIGGRAPH, 2007.
[11] A. Coates and A. Ng. The importance of encoding versus training with sparse coding and vector quantization. ICML, 2011.
[12] N. Dalal and B. Triggs. Histograms of oriented gradients for
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22] human detection. ICCV, 2005. C. Dubout and F. Fleuret. Exact acceleration of linear object detectors. ECCV, 2012. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The PASCAL Visual Object Classes Challenge. http://pascallin.ecs.soton.ac.uk/challenges/VOC/. C. C. Fowlkes, C. L. Luengo Hendriks, S. V. E. Ker a¨nen, G. H. Weber, O. R ¨ubel, M.-Y. Huang, S. Chatoor, A. H. DePace, L. Simirenko, C. Henriquez, A. Beaton, R. Weiszmann, S. Celniker, B. Hamann, D. W. Knowles, M. D. Biggin, M. Eisen, and J. Malik. A quantitative spatiotemporal atlas of gene expression in the drosophila blastoderm. Cell, 133(2), 2008. A. Hiang, C. Lin, C. Chuang, C. H., C. Hsieh, Y. C., S. C., J. Wu, W. G., and Y. Chen. Three-dimensional reconstruction of brain-wide wiring networks in drosophila at singlecell resolution. Curr. Biol., 21, 2011. P. Kr ¨ahenb u¨hl and V. Koltun. Efficient inference in fully connected crfs with gaussian edge potentials. NIPS, 2011. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. CVPR, 2006. T. Leung and J. Malik. Recognizing surfaces using threedimensional textons. ICCV, 1999. F. Long, H. Peng, X. Liu, S. Kim, and E. Myers. A 3D digital atlas of C. elegans and its application to single-cell analyses. Nature Methods, 6(9), 2009. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004. J. Malik and P. Perona. Preattentive texture discrimination with early vision mechanisms. JOSA A, 1990.
[23] E. Tola, V. Lepetit, and P. Fua. Daisy: An efficient dense descriptor applied to wide-baseline stereo. TPAMI, 2010.
[24] K. E. A. van de Sande, T. Gevers, and C. G. M. Snoek. Evaluating color descriptors for object and scene recognition. TPAMI, 2010.
[25] A. Vazquez-Reina, M. Gelbart, D. Huang, J. Lichtman, E. Miller, and H. Pfiste. Segmentation fusion for connectomics. ICCV, 2011.
[26] S. Vitaladevuni and R. Basri. Co-clustering of image segments using convex optimization applied to EM neuronal reconstruction. CVPR, 2010. 33444558