Abstract
We present an object recognition system which is capable of on-line learning of representations of scenes and objects from natural image sequences. Local appearance features are used in a tracking framework to find ‘key-frames’ of the input sequence during learning. In addition, the same basic framework is used for both learning and recognition. The system creates sparse representations and shows good recognition performance in a variety of viewing conditions for a database of natural image sequences.
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
A. Baerveldt, “A vision system for object verification and localization based on local features”, Robotics and Autonomous Systems, 34(2-3): 83–92, 2001.
D. Jugessur, G. Dudek, “Local Appearance for Robust Object Recognition”, In Proc. CVPR’00, 834–839, 2000.
J. Koenderink, A. van Doorn, “The internal representation of solid shape with respect to vision”, Biological Cybernetics, 32, 1979.
D. Lowe, “toward a Computational Model for Object Recognition in IT Cortex”, In Proc. BMCV’00, 20–31, 2000.
A. Massad, B. Mertsching, and S. Schmalz, “Combining multiple views and temporal associations for 3-D object recognition”, In Proc. ECCV’98, 699–715, 1998.
B. Mel, “SEEMORE: Combining color, shape, and texture histogramming in a neurally-inspired approach to visual object recognition”, Neural Computation, 9:777–804, 1997.
M. Pilu, “A direct method for stereo correspondence based on singular value decomposition”, In Proc. CVPR’97, 261–266, 1997.
C. Schmid, R. Mohr, “Local Greyvalue Invariants for Image Retrieval”, IEEE TPAMI, 19(5):530–535, 1997.
G. Scott, H. Longuet-Higgins, “An algorithm for associating the features of two images”, In Proc. Royal Society of London, B(244):21–26, 1991.
C. Tomasi, T. Kanade, “Detection and tracking of point features”, Carnegie-Mellon Tech Report CMU-CS-91-132, 1991.
T. Tuytelaars, L. van Gool, “Content-based image retrieval based on local affinely invariant regions”, In Proc. Visual’ 99, 493–500, 1999.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wallraven, C., Bülthoff, H. (2001). Acquiring Robust Representations for Recognition from Image Sequences. In: Radig, B., Florczyk, S. (eds) Pattern Recognition. DAGM 2001. Lecture Notes in Computer Science, vol 2191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45404-7_29
Download citation
DOI: https://doi.org/10.1007/3-540-45404-7_29
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42596-0
Online ISBN: 978-3-540-45404-5
eBook Packages: Springer Book Archive