Sciweavers

MICAI
2010
Springer
13 years 11 months ago
Object Class Recognition Using SIFT and Bayesian Networks
Several methods have been presented in the literature that successfully used SIFT features for object identification, as they are reasonably invariant to translation, rotation, sc...
Leonardo Chang, Miriam Monica Duarte, Luis Enrique...
DICTA
2008
14 years 2 months ago
Exploiting Part-Based Models and Edge Boundaries for Object Detection
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...
Josephine Sullivan, Oscar M. Danielsson, Stefan Ca...
CLOR
2006
14 years 2 months ago
An Implicit Shape Model for Combined Object Categorization and Segmentation
We present a method for object categorization in real-world scenes. Following a common consensus in the field, we do not assume that a figure-ground segmentation is available prior...
Bastian Leibe, Ales Leonardis, Bernt Schiele
AAAI
2008
14 years 2 months ago
A Fast Data Collection and Augmentation Procedure for Object Recognition
When building an application that requires object class recognition, having enough data to learn from is critical for good performance, and can easily determine the success or fai...
Benjamin Sapp, Ashutosh Saxena, Andrew Y. Ng
ACCV
2007
Springer
14 years 6 months ago
Hierarchical Learning of Dominant Constellations for Object Class Recognition
Abstract. The importance of spatial configuration information for object class recognition is widely recognized. Single isolated local appearance codes are often ambiguous. On the...
Nathan Mekuz, John K. Tsotsos
ICCV
2005
IEEE
15 years 2 months ago
Local Features for Object Class Recognition
In this paper we compare the performance of local detectors and descriptors in the context of object class recognition. Recently, many detectors / descriptors have been evaluated ...
Krystian Mikolajczyk, Bastian Leibe, Bernt Schiele
CVPR
2007
IEEE
15 years 2 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
CVPR
2006
IEEE
15 years 2 months ago
Multiple Object Class Detection with a Generative Model
In this paper we propose an approach capable of simultaneous recognition and localization of multiple object classes using a generative model. A novel hierarchical representation ...
Krystian Mikolajczyk, Bastian Leibe, Bernt Schiele
CVPR
2005
IEEE
15 years 2 months ago
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
Wei Zhang 0002, Bing Yu, Gregory J. Zelinsky, Dimi...
CVPR
2005
IEEE
15 years 2 months ago
Fast Spatial Pattern Discovery Integrating Boosting with Constellations of Contextual Descriptors
We present a novel approach for fast object class recognition incorporating contextual information into boosting. The object is represented as a constellation of generalized corre...
Jaume Amores, Nicu Sebe, Petia Radeva