Abstract
We study the task of interactive semantic labeling of a segmentation hierarchy. To this end we propose a framework interleaving two components: an automatic labeling step, based on a Conditional Random Field whose dependencies are defined by the inclusion tree of the segmentation hierarchy, and an interaction step that integrates incremental input from a human user. Evaluated on two distinct datasets, the proposed interactive approach efficiently integrates human interventions and illustrates the advantages of structured prediction in an interactive framework.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Arbelaez, P., Maire, M., Fowlkes, C., Malik, J.: Contour detection and hierarchical image segmentation. PAMI 33(5), 898–916 (2011)
Branson, S., Perona, P., Belongie, S.: Strong supervision from weak annotation: Interactive training of deformable part models. In: ICCV, pp. 1832–1839 (2011)
Brostow, G.J., Fauqueur, J., Cipolla, R.: Semantic object classes in video: A high-definition ground truth database. PRL 30(2), 88–97 (2009)
Brostow, G.J., Shotton, J., Fauqueur, J., Cipolla, R.: Segmentation and Recognition Using Structure from Motion Point Clouds. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 44–57. Springer, Heidelberg (2008)
Carreira, J., Li, F., Sminchisescu, C.: Object Recognition by Sequential Figure-Ground Ranking. IJCV, 1–20 (2011)
Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The pascal visual object classes (voc) challenge. IJCV 88(2), 303–338 (2010)
Gonfaus, J., Boix, X., van de Weijer, J., Bagdanov, A., Serrat, J., Gonzàndlez, J.: Harmony potentials for joint classification and segmentation. In: CVPR, pp. 3280–3287 (2010)
Gould, S., Fulton, R., Koller, D.: Decomposing a scene into geometric and semantically consistent regions. In: ICCV, pp. 1–8 (2009)
Haxhimusa, Y., Kropatsch, W.: Hierarchy of Partitions with Dual Graph Contraction. In: Michaelis, B., Krell, G. (eds.) DAGM 2003. LNCS, vol. 2781, pp. 338–345. Springer, Heidelberg (2003)
Hoiem, D., Efros, A.A., Hebert, M.: Geometric context from a single image. In: ICCV, pp. 654–661 (2005)
Ion, A., Carreira, J., Sminchisescu, C.: Probabilistic joint image segmentation and labeling. In: NIPS, pp. 1827–1835 (2011)
Ladický, L., Russell, C., Kohli, P., Torr, P.: Associative hierarchical CRFs for object class image segmentation. In: ICCV, pp. 739–746 (2009)
Malisiewicz, T., Efros, A.A.: Improving spatial support for objects via multiple segmentations. In: BMVC (2007)
McAuley, J., de Campos, T., Csurka, G., Perronnin, F.: Hierarchical image-region labeling via structured learning. In: BMVC (2009)
Mensink, T., Verbeek, J., Csurka, G.: Learning structured prediction models for interactive image labeling. In: CVPR, pp. 833–840 (2011)
Nowozin, S., Gehler, P.V., Lampert, C.H.: On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part VI. LNCS, vol. 6316, pp. 98–111. Springer, Heidelberg (2010)
Pearl, J.: Fusion, propagation, and structuring in belief networks. AI 29(3), 241–288 (1986)
Plath, N., Toussaint, M., Nakajima, S.: Multi-class image segmentation using conditional random fields and global classification. In: ICML, pp. 817–824 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zankl, G., Haxhimusa, Y., Ion, A. (2012). Interactive Labeling of Image Segmentation Hierarchies. In: Pinz, A., Pock, T., Bischof, H., Leberl, F. (eds) Pattern Recognition. DAGM/OAGM 2012. Lecture Notes in Computer Science, vol 7476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32717-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-32717-9_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32716-2
Online ISBN: 978-3-642-32717-9
eBook Packages: Computer ScienceComputer Science (R0)