Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
Machine Learning - Special issue on inductive transfer
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
A Trainable System for Object Detection
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A statistical approach to 3d object detection applied to faces and cars
A statistical approach to 3d object detection applied to faces and cars
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Affine-Invariant Local Descriptors and Neighborhood Statistics for Texture Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Object Recognition with Informative Features and Linear Classification
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Robust Real-Time Face Detection
International Journal of Computer Vision
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Learning to Detect Objects in Images via a Sparse, Part-Based Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning From a Small Number of Training Examples by Exploiting Object Categories
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 6 - Volume 06
Cross-Generalization: Learning Novel Classes from a Single Example by Feature Replacement
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Part-Based Statistical Models for Object Classification and Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Learning Hierarchical Models of Scenes, Objects, and Parts
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Learning methods for generic object recognition with invariance to pose and lighting
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Sharing features: efficient boosting procedures for multiclass object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Uncovering shared structures in multiclass classification
Proceedings of the 24th international conference on Machine learning
Hypergraph spectral learning for multi-label classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Multiclass Adaboost and Coupled Classifiers for Object Detection
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Collaborative learning for image and video annotation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
International Journal of Computer Vision
Multi Activity Recognition Based on Bodymodel-Derived Primitives
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Cue Integration for Urban Area Extraction in Remote Sensing Images
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Regional category parsing in undirected graphical models
Pattern Recognition Letters
Computer Vision and Image Understanding
Learning with Few Examples by Transferring Feature Relevance
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Image-based street-side city modeling
ACM SIGGRAPH Asia 2009 papers
Image categorization combining neighborhood methods and boosting
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Traffic sign recognition using evolutionary adaboost detection and forest-ECOC classification
IEEE Transactions on Intelligent Transportation Systems
A first glimpse of cryptography's Holy Grail
Communications of the ACM
Using the forest to see the trees: exploiting context for visual object detection and localization
Communications of the ACM
Semi---supervised Learning with Constraints for Multi---view Object Recognition
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Combining Appearance and Range Based Information for Multi-class Generic Object Recognition
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Optical Flow Based Detection in Mixed Human Robot Environments
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Scalable learning for object detection with GPU hardware
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
The Pascal Visual Object Classes (VOC) Challenge
International Journal of Computer Vision
Learning 3D mesh segmentation and labeling
ACM SIGGRAPH 2010 papers
Boosting with temporal consistent learners: an application to human activity recognition
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Inter-robot transfer learning for perceptual classification
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A novel learning approach to multiple tasks based on boosting methodology
Pattern Recognition Letters
Original paper: Real time feature extraction and Standard Cutting Models fitting in grape leaves
Computers and Electronics in Agriculture
Backprojection revisited: scalable multi-view object detection and similarity metrics for detections
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Avoiding confusing features in place recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Efficient object category recognition using classemes
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Monocular 3D scene modeling and inference: understanding multi-object traffic scenes
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Active mask hierarchies for object detection
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
A coarse-to-fine taxonomy of constellations for fast multi-class object detection
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Pattern Recognition Letters
Human posture recognition for intelligent vehicles
Journal of Real-Time Image Processing
One-shot learning of object categories using dependent Gaussian processes
Proceedings of the 32nd DAGM conference on Pattern recognition
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
Probabilistic reasoning for assembly-based 3D modeling
ACM SIGGRAPH 2011 papers
Texture-lobes for tree modelling
ACM SIGGRAPH 2011 papers
A Numerical Study of the Bottom-Up and Top-Down Inference Processes in And-Or Graphs
International Journal of Computer Vision
Red-eyes removal through cluster-based boosting on gray codes
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
Fast object detection using steiner tree
Machine Graphics & Vision International Journal
Detection performance evaluation of boosted random ferns
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Feature set search space for fuzzyboost learning
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Passive and In-Situ assessment of mental and physical well-being using mobile sensors
Proceedings of the 13th international conference on Ubiquitous computing
Semantic hierarchies for image annotation: A survey
Pattern Recognition
Multi-class object detection with hough forests using local histograms of visual words
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Embedding Gestalt laws on conditional random field for image segmentation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
MIRAGE'11 Proceedings of the 5th international conference on Computer vision/computer graphics collaboration techniques
Learning hatching for pen-and-ink illustration of surfaces
ACM Transactions on Graphics (TOG)
Cross-Articulation learning for robust detection of pedestrians
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Online multiple tasks one-shot learning of object categories and vision
Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia
Real-time viewpoint-invariant hand localization with cluttered backgrounds
Image and Vision Computing
Automatic microcalcification and cluster detection for digital and digitised mammograms
Knowledge-Based Systems
Boosting for transfer learning from multiple data sources
Pattern Recognition Letters
Part-Based object detection using cascades of boosted classifiers
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Road image segmentation and recognition using hierarchical bag-of-textons method
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
Foundations and Trends® in Computer Graphics and Vision
Class consistent k-means: Application to face and action recognition
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Fast shared boosting for large-scale concept detection
Multimedia Tools and Applications
International Journal of Computer Vision
Transfer Learning from Unlabeled Data via Neural Networks
Neural Processing Letters
Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot
Journal of Intelligent and Robotic Systems
Filter-Based mean-field inference for random fields with higher-order terms and product label-spaces
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Shape sharing for object segmentation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Efficient training of graph-regularized multitask SVMs
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
A tree-based approach to integrated action localization, recognition and segmentation
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Adaptive object detection by implicit sub-class sharing features
Signal Processing
Enhanced representation and multi-task learning for image annotation
Computer Vision and Image Understanding
Cross-Database transfer learning via learnable and discriminant error-correcting output codes
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Combining fast extracted edge descriptors and feature sharing for rapid object detection
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
A tutorial on human activity recognition using body-worn inertial sensors
ACM Computing Surveys (CSUR)
Recognizing hand gestures using the weighted elastic graph matching (WEGM) method
Image and Vision Computing
A unified tree-based framework for joint action localization, recognition and segmentation
Computer Vision and Image Understanding
Learning and parsing video events with goal and intent prediction
Computer Vision and Image Understanding
HEGM: A hierarchical elastic graph matching for hand gesture recognition
Pattern Recognition
Tagging-by-search: automatic image region labeling using gaze information obtained from image search
Proceedings of the 19th international conference on Intelligent User Interfaces
Fast semantic object search and detection for vegetable trading information using Steiner tree
Artificial Intelligence Review
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We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifiers to the image, at multiple locations and scales. This can be slow and can require a lot of training data since each classifier requires the computation of many different image features. In particular, for independently trained detectors, the (runtime) computational complexity and the (training-time) sample complexity scale linearly with the number of classes to be detected. We present a multitask learning procedure, based on boosted decision stumps, that reduces the computational and sample complexity by finding common features that can be shared across the classes (and/or views). The detectors for each class are trained jointly, rather than independently. For a given performance level, the total number of features required and, therefore, the runtime cost of the classifier, is observed to scale approximately logarithmically with the number of classes. The features selected by joint training are generic edge-like features, whereas the features chosen by training each class separately tend to be more object-specific. The generic features generalize better and considerably reduce the computational cost of multiclass object detection.