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» Dataset Issues in Object Recognition
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ICPR
2010
IEEE
14 years 2 months ago
Object Recognition and Localization Via Spatial Instance Embedding
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Nazli Ikizler Cinbis, Stan Sclaroff
ECCV
2010
Springer
14 years 28 days ago
Object, Scene and Actions: Combining Multiple Features for Human Action Recognition
Abstract. In many cases, human actions can be identified not only by the singular observation of the human body in motion, but also properties of the surrounding scene and the rel...

Publication
172views
12 years 2 months ago
Beyond Straight Lines - Object Detection using Curvature
We present an approach that directly uses curvature cues in a discriminative way to perform object recognition. We show that integrating curvature information substantially impr...
Antonio Monroy, Angela Eigenstetter and Björn Omm...
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
14 years 8 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
IJCV
2008
241views more  IJCV 2008»
13 years 8 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe