PR
2008
13 years 11 months ago
2008
We present a method for object class detection in images based on global shape. A distance measure for elastic shape matching is derived, which is invariant to scale and rotation,...
IJCV
2000
13 years 11 months ago
2000
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
NIPS
2001
14 years 24 days ago
2001
Recent work has shown impressive transform-invariant modeling and clustering for sets of images of objects with similar appearance. We seek to expand these capabilities to sets of...
DICTA
2008
14 years 27 days ago
2008
This paper explores how to exploit shape information to perform object class recognition. We use a sparse partbased model to describe object categories defined by shape. The spars...
ICIAR
2004
Springer
14 years 4 months ago
2004
Springer
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
ICCV
2007
IEEE
14 years 5 months ago
2007
IEEE
We consider clustering situations in which the pairwise affinity between data points depends on a latent ”context” variable. For example, when clustering features arising fro...
CAIP
2009
Springer
14 years 6 months ago
2009
Springer
Most object detection techniques discussed in the literature are based solely on texture-based features that capture the global or local appearance of an object. While results indi...
CVPR
2010
IEEE
14 years 6 months ago
2010
IEEE
This paper presents a new approach for multi-view object class detection. Appearance and geometry are treated as separate learning tasks with different training data. Our approach...
ECCV
2008
Springer
15 years 1 months ago
2008
Springer
Abstract. An important task in object recognition is to enable algorithms to categorize objects under arbitrary poses in a cluttered 3D world. A recent paper by Savarese & Fei-...
ICCV
2007
IEEE
15 years 1 months ago
2007
IEEE
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...