Boosting Chain Learning for Object Detection

Authors:
Rong Xiao;Long Zhu;Hong-Jiang Zhang
Affiliations:
-;-;-
Venue:
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Year:
2003

Citing 0
Cited 29

Face Recognition Using Laplacianfaces

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face-tracking as an augmented input in video games: enhancing presence, role-playing and control

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
High-Performance Rotation Invariant Multiview Face Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Design of Cascades of Boosted Ensembles for Face Detection

International Journal of Computer Vision
Improving relevance judgment of web search results with image excerpts

Proceedings of the 17th international conference on World Wide Web
Learning Fast Emulators of Binary Decision Processes

International Journal of Computer Vision
Asymmetric Learning for Pedestrian Detection Based on Joint Local Orientation Histograms

ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Multiple classifier object detection with confidence measures

AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Learning to detect aircraft at low resolutions

ICVS'08 Proceedings of the 6th international conference on Computer vision systems
A reconfigurable architecture for rotation invariant multi-view face detection based on a novel two-stage boosting method

EURASIP Journal on Advances in Signal Processing
2D staircase detection using real adaboost

ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems

IEEE Transactions on Image Processing
Automatic cascade training with perturbation bias

CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Framework for research on detection classifiers

Proceedings of the 24th Spring Conference on Computer Graphics
Fast rotation invariant multi-view face detection based on real adaboost

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
3D shape constraint for facial feature localization using probabilistic-like output

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Asymmetric totally-corrective boosting for real-time object detection

ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Fast human detection based on enhanced variable size HOG features

ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Automatic citrus canker detection from leaf images captured in field

Pattern Recognition Letters
Towards optimal training of cascaded detectors

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Face detection method based on kernel independent component analysis and boosting chain algorithm

ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
A boosting SVM chain learning for visual information retrieval

ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Probabilistic cascade random fields for man-made structure detection

ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
A novel distribution-based feature for rapid object detection

Neurocomputing
Making a Shallow Network Deep: Conversion of a Boosting Classifier into a Decision Tree by Boolean Optimisation

International Journal of Computer Vision
Efficient and accurate face detection using heterogeneous feature descriptors and feature selection

Computer Vision and Image Understanding
Crosstalk cascades for frame-rate pedestrian detection

ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
A survey on recent object detection techniques useful for monocular vision-based planetary terrain classification

Robotics and Autonomous Systems
A biased selection strategy for information recycling in Boosting cascade visual-object detectors

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

A general classification framework, called boostingchain, is proposed for learning boosting cascade. In thisframework, a "chain" structure is introduced to integratehistorical knowledge into successive boosting learning.Moreover, a linear optimization scheme is proposed toaddress the problems of redundancy in boosting learningand threshold adjusting in cascade coupling. By thismeans, the resulting classifier consists of fewer weakclassifiers yet achieves lower error rates than boostingcascade in both training and test. Experimentalcomparisons of boosting chain and boosting cascade areprovided through a face detection problem. Thepromising results clearly demonstrate the effectivenessmade by boosting chain.