Machine Learning
Summed-area tables for texture mapping
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Robust Real-Time Face Detection
International Journal of Computer Vision
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
Putting Objects in Perspective
International Journal of Computer Vision
Efficient Subwindow Search: A Branch and Bound Framework for Object Localization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using the forest to see the trees: exploiting context for visual object detection and localization
Communications of the ACM
The Pascal Visual Object Classes (VOC) Challenge
International Journal of Computer Vision
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-stage sampling with boosting cascades for pedestrian detection in images and videos
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Regression forests for efficient anatomy detection and localization in CT studies
MCV'10 Proceedings of the 2010 international MICCAI conference on Medical computer vision: recognition techniques and applications in medical imaging
Hough Forests for Object Detection, Tracking, and Action Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards optimal training of cascaded detectors
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
A coarse-to-fine approach for fast deformable object detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Recognition using visual phrases
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Real time head pose estimation with random regression forests
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Efficient regression of general-activity human poses from depth images
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Learning a category independent object detection cascade
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Segmentation as selective search for object recognition
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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State-of-the-art methods for object detection are mostly based on an expensive exhaustive search over the image at different scales. In order to reduce the computational time, one can perform a selective search to obtain a small subset of relevant object hypotheses that need to be evaluated by the detector. For that purpose, we employ a regression to predict possible object scales and locations by exploiting the local context of an image. Furthermore, we show how a priori information, if available, can be integrated to improve the prediction. The experimental results on three datasets including the Caltech pedestrian and PASCAL VOC dataset show that our method achieves the detection performance of an exhaustive search approach with much less computational load. Since we model the prior distribution over the proposals locally, it generalizes well and can be successfully applied across datasets.