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» Contour-Based Learning for Object Detection
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CVPR
2011
IEEE
13 years 5 months ago
Learning to Recognize Objects in Egocentric Activities
This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
Alireza Fathi, Xiaofeng Ren, James Rehg
ICPR
2004
IEEE
14 years 10 months ago
Object Recognition Using Segmentation for Feature Detection
: A new method is presented to learn object categories from unlabeled and unsegmented images for generic object recognition. We assume that each object can be characterized by a se...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
ICCV
2007
IEEE
14 years 10 months ago
High Detection-rate Cascades for Real-Time Object Detection
A new strategy is proposed for the design of cascaded object detectors of high detection-rate. The problem of jointly minimizing the false-positive rate and classification complex...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
DAGM
2006
Springer
14 years 14 days ago
Cross-Articulation Learning for Robust Detection of Pedestrians
Recognizing categories of articulated objects in real-world scenarios is a challenging problem for today's vision algorithms. Due to the large appearance changes and intra-cla...
Edgar Seemann, Bernt Schiele
CVPR
2012
IEEE
11 years 11 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