Sciweavers

321 search results - page 18 / 65
» Object Detection Combining Recognition and Segmentation
Sort
View
DICTA
2009
13 years 8 months ago
SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images
Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose fo...
Edmond Zhang, Michael Mayo
CLOR
2006
13 years 11 months ago
Comparison of Generative and Discriminative Techniques for Object Detection and Classification
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the dis...
Ilkay Ulusoy, Christopher M. Bishop
ICCV
2005
IEEE
14 years 9 months ago
Identifying Individuals in Video by Combining "Generative" and Discriminative Head Models
The objective of this work is automatic detection and identification of individuals in unconstrained consumer video, given a minimal number of labelled faces as training data. Whi...
Mark Everingham, Andrew Zisserman
SPIESR
2001
133views Database» more  SPIESR 2001»
13 years 9 months ago
Shot detection combining Bayesian and structural information
There are a number of shots in a video, each of which has boundary types, such as cut, fade, dissolve and wipe. Many previous approaches can find the cut boundary without difficul...
Seung-Hoon Han, In-So Kweon
ICCV
2005
IEEE
14 years 9 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu