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» Object detection at multiple scales improves accuracy
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ICCV
2009
IEEE
16 years 2 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
CVPR
2007
IEEE
15 years 1 months ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
CVPR
2007
IEEE
15 years 11 months ago
A boosting regression approach to medical anatomy detection
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
Shaohua Kevin Zhou, Jinghao Zhou, Dorin Comaniciu
ICVGIP
2008
14 years 11 months ago
Object Category Recognition with Projected Texture
Recognition of object categories from their images is extremely challenging due to the large intra-class variations, and variations in pose, illumination and scale, in addition to...
Avinash Sharma, Anoop M. Namboodiri
ECCV
2008
Springer
15 years 11 months ago
Multi-scale Improves Boundary Detection in Natural Images
In this work we empirically study the multi-scale boundary detection problem in natural images. We utilize local boundary cues including contrast, localization and relative contras...
Xiaofeng Ren