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NIPS
2004
13 years 10 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
NIPS
2004
13 years 10 months ago
The power of feature clustering: An application to object detection
We give a fast rejection scheme that is based on image segments and demonstrate it on the canonical example of face detection. However, instead of focusing on the detection step w...
Shai Avidan, Moshe Butman
MM
2003
ACM
239views Multimedia» more  MM 2003»
14 years 2 months ago
Foreground object detection from videos containing complex background
This paper proposes a novel method for detection and segmentation of foreground objects from a video which contains both stationary and moving background objects and undergoes bot...
Liyuan Li, Weimin Huang, Irene Y. H. Gu, Qi Tian
DCC
2008
IEEE
14 years 8 months ago
Object-Based Regions of Interest for Image Compression
A fully automated architecture for object-based region of interest (ROI) detection is proposed. ROI's are defined as regions containing user defined objects of interest, and ...
Sunhyoung Han, Nuno Vasconcelos
RAS
2010
115views more  RAS 2010»
13 years 7 months ago
Learning grasping points with shape context
This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and ...
Jeannette Bohg, Danica Kragic