Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
IEEE Transactions on Pattern Analysis and Machine Intelligence
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
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
An extension of the Munkres algorithm for the assignment problem to rectangular matrices
Communications of the ACM
Probabilistic Methods for Finding People
International Journal of Computer Vision
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Qualitative and Quantitative Car Tracking from a Range Image Sequence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Detecting Pedestrians Using Patterns of Motion and Appearance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pedestrian Detection in Crowded Scenes
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
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Human Detection Using a Cascade of Histograms of Oriented Gradients
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Multimodal people detection and tracking in crowded scenes
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Monocular Pedestrian Detection: Survey and Experiments
IEEE Transactions on Pattern Analysis and Machine Intelligence
LIDAR and vision-based pedestrian detection system
Journal of Field Robotics
Tracking groups of people with a multi-model hypothesis tracker
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Detecting pedestrians at very small scales
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Tracking-based semi-supervised learning
International Journal of Robotics Research
Fusing LIDAR, camera and semantic information: A context-based approach for pedestrian detection
International Journal of Robotics Research
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This paper presents a novel approach to detect and track people and cars based on the combined information retrieved from a camera and a laser range scanner. Laser data points are classified by using boosted Conditional Random Fields, while the image based detector uses an extension of the Implicit Shape Model (ISM), which learns a codebook of local descriptors from a set of hand-labeled images and uses them to vote for centers of detected objects. Our extensions to ISM include the learning of object parts and template masks to obtain more distinctive votes for the particular object classes. The detections from both sensors are then fused and the objects are tracked using a Kalman Filter with multiple motion models. Experiments conducted in real-world urban scenarios demonstrate the effectiveness of our approach.