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» Learning to Recognize Objects
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NIPS
2004
15 years 6 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...
PAMI
2007
210views more  PAMI 2007»
15 years 4 months ago
Sharing Visual Features for Multiclass and Multiview Object Detection
We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifier...
Antonio Torralba, Kevin P. Murphy, William T. Free...
BMVC
2010
15 years 3 months ago
Accounting for the Relative Importance of Objects in Image Retrieval
We introduce a method for image retrieval that leverages the implicit information about object importance conveyed by the list of keyword tags a person supplies for an image. We p...
Sung Ju Hwang, Kristen Grauman
CVPR
2012
IEEE
13 years 7 months ago
Discovering important people and objects for egocentric video summarization
We present a video summarization approach for egocentric or “wearable” camera data. Given hours of video, the proposed method produces a compact storyboard summary of the came...
Yong Jae Lee, Joydeep Ghosh, Kristen Grauman
ICRA
2010
IEEE
220views Robotics» more  ICRA 2010»
15 years 2 months ago
General object tracking with a component-based target descriptor
In this paper, we present a component-based visual object tracker for mobile platforms. The core of the technique is a component-based descriptor that captures the structure and ap...
Simone Frintrop