Part-whole relations in object-centered systems: an overview
Data & Knowledge Engineering - Special issue on modeling parts and wholes
Learning in graphical models
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a Sparse Representation for Object Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Unsupervised Learning of Models for Recognition
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Selection of Scale-Invariant Parts for Object Class Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Shape Matching and Object Recognition Using Low Distortion Correspondences
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
Contour-Based Learning for Object Detection
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Creating Efficient Codebooks for Visual Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Object Categorization by Learned Universal Visual Dictionary
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Generic Object Recognition with Boosting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiclass Object Recognition with Sparse, Localized Features
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Multiple Object Class Detection with a Generative Model
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Design and Performance of a Fault-Tolerant Real-Time CORBA Event Service
ECRTS '06 Proceedings of the 18th Euromicro Conference on Real-Time Systems
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
International Journal of Computer Vision
Robust Object Recognition with Cortex-Like Mechanisms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Robust Object Detection with Interleaved Categorization and Segmentation
International Journal of Computer Vision
Multiscale Categorical Object Recognition Using Contour Fragments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel Codebooks for Scene Categorization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
International Journal of Computer Vision
Learning non-redundant codebooks for classifying complex objects
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hyperfeatures – multilevel local coding for visual recognition
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Adapted vocabularies for generic visual categorization
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
A boundary-fragment-model for object detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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Categorizing visual elements is fundamentally important for autonomous mobile robots to get intelligence such as novel object learning and topological place recognition. The main difficulties of visual categorization are two folds: large internal and external variations caused by surface markings and background clutters, respectively. In this paper, we present a new object categorization method robust to surface markings and background clutters. Biologically motivated codebook selection method alleviates the surface marking problem. Introduction of visual context to the codebook approach can handle the background clutter issue. The visual contexts utilized are part-part context, part-whole context, and object-background context. The additional contribution is the proposition of a statistical optimization method, termed boosted MCMC, to incorporate the visual context in the codebook approach. In this framework, three kinds of contexts are incorporated. The object category label and figure-ground information are estimated to best describe input images. We experimentally validate the effectiveness and feasibility of object categorization in cluttered environments.