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» Object Recognition using Junctions
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ICCV
2005
IEEE
15 years 11 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
ROBOCUP
2007
Springer
162views Robotics» more  ROBOCUP 2007»
15 years 4 months ago
Adaptive Recognition of Color-Coded Objects in Indoor and Outdoor Environments
Abstract. To achieve robust color perception under varying light conditions in indoor and outdoor environments, we propose a three-step method consisting of adaptive camera paramet...
Yasutake Takahashi, Walter Nowak, Thomas Wisspeint...
ICCV
2009
IEEE
16 years 2 months ago
What is the Best Multi-Stage Architecture for Object Recognition?
In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear transformation, and some sort of feature pooling layer...
Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio R...
ICCV
2011
IEEE
13 years 10 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
3DPVT
2006
IEEE
247views Visualization» more  3DPVT 2006»
15 years 1 months ago
Contour-Based Object Detection in Range Images
This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extracti...
Stefan Stiene, Kai Lingemann, Andreas Nüchter...