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CVPR
2007
IEEE
15 years 11 months ago
Detecting Pedestrians by Learning Shapelet Features
In this paper, we address the problem of detecting pedestrians in still images. We introduce an algorithm for learning shapelet features, a set of mid?level features. These featur...
Payam Sabzmeydani, Greg Mori
CVPR
2012
IEEE
12 years 12 months ago
Image categorization using Fisher kernels of non-iid image models
The bag-of-words (BoW) model treats images as an unordered set of local regions and represents them by visual word histograms. Implicitly, regions are assumed to be identically an...
Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia...
ICRA
2002
IEEE
177views Robotics» more  ICRA 2002»
15 years 2 months ago
Robust Vision-Based Localization for Mobile Robots using an Image Retrieval System Based on Invariant Features
In this paper we present a vision-based approach to mobile robot localization, that integrates an image retrieval system with Monte-Carlo localization. The image retrieval process...
Jürgen Wolf, Wolfram Burgard, Hans Burkhardt
IBPRIA
2009
Springer
15 years 2 months ago
Local Boosted Features for Pedestrian Detection
The present paper addresses pedestrian detection using local boosted features that are learned from a small set of training images. Our contribution is to use two boosting steps. T...
Michael Villamizar, Alberto Sanfeliu, Juan Andrade...
ICIP
1997
IEEE
15 years 11 months ago
Wavelet features for statistical object localization without segmentation
This paper describes a new technique for statistical 3{D object localization. Local feature vectors are extracted for all image positions, in contrast to segmentation in classical...
Heinrich Niemann, Josef Pösl