Contextual Priming for Object Detection
International Journal of Computer Vision
Robust Real-Time Face Detection
International Journal of Computer Vision
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Integrating Representative and Discriminative Models for Object Category Detection
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
A detector tree of boosted classifiers for real-time object detection and tracking
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
International Journal of Computer Vision
Large Scale Multiple Kernel Learning
The Journal of Machine Learning Research
Multiclass multiple kernel learning
Proceedings of the 24th international conference on Machine learning
Representing shape with a spatial pyramid kernel
Proceedings of the 6th ACM international conference on Image and video retrieval
Groups of Adjacent Contour Segments for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pedestrian recognition from a moving catadioptric camera
Proceedings of the 29th DAGM conference on Pattern recognition
Learning of graphical models and efficient inference for object class recognition
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Feature Selection for Density Level-Sets
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Medical image classification with multiple kernel learning
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Multi-task learning via non-sparse multiple kernel learning
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Efficient classification of images with taxonomies
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
On Taxonomies for Multi-class Image Categorization
International Journal of Computer Vision
Enhanced representation and multi-task learning for image annotation
Computer Vision and Image Understanding
A robust image classification scheme with sparse coding and multiple kernel learning
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
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Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an image purely on a per-class basis. Joint learning of more than one object class would generally be preferable, since this would allow the use of contextual information such as co-occurrence between classes. However, this approach is usually not employed because of its computational cost.In this paper we propose a method to combine the efficiency of single class localization with a subsequent decision process that works jointly for all given object classes. By following a multiple kernel learning (MKL) approach, we automatically obtain a sparse dependency graph of relevant object classes on which to base the decision. Experiments on the PASCAL VOC 2006 and 2007 datasets show that the subsequent joint decision step clearly improves the accuracy compared to single class detection.