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» Object detection at multiple scales improves accuracy
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ICCV
2009
IEEE
16 years 4 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 3 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
16 years 1 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
15 years 1 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
16 years 1 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