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» Object Detection Using Multi-local Feature Manifolds
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ECCV
2008
Springer
16 years 4 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
155
Voted
GIS
2009
ACM
15 years 6 months ago
Next generation map making: geo-referenced ground-level LIDAR point clouds for automatic retro-reflective road feature extractio
This paper presents a novel method to process large scale, ground level Light Detection and Ranging (LIDAR) data to automatically detect geo-referenced navigation attributes (traf...
Xin Chen, Brad Kohlmeyer, Matei Stroila, Narayanan...
164
Voted
CVPR
2009
IEEE
16 years 9 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese
115
Voted
ICPR
2002
IEEE
16 years 3 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
157
Voted
ICDAR
2003
IEEE
15 years 7 months ago
Word Segmentation of Handwritten Dates in Historical Documents by Combining Semantic A-Priori-Knowledge with Local Features
The recognition of script in historical documents requires suitable techniques in order to identify single words. Segmentation of lines and words is a challenging task because lin...
Markus Feldbach, Klaus D. Tönnies