Fast Feature Pyramids for Object Detection

Multi-resolution image features may be approximated via extrapolation from nearby scales, rather than being computed explicitly. This fundamental insight allows us to design object detection algorithms that are as accurate, and considerably faster, than the state-of-the-art. The computational bottle...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 36; H. 8; S. 1532 - 1545
Hauptverfasser:	Dollar, Piotr, Appel, Ron, Belongie, Serge, Perona, Pietro
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Los Alamitos, CA IEEE 01.08.2014 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Approximation Approximation methods Artificial intelligence Computation Computer science; control theory; systems Detectors Exact sciences and technology Feature extraction Histograms image pyramids Mathematical analysis natural image statistics Object detection Pattern recognition. Digital image processing. Computational geometry pedestrian detection Pyramids real-time systems Spectra Texture Theoretical computing Visual features Visual task performance Visualization Bottleneck Computer vision Image recognition Image resolution Statistical analysis Image processing Visual features pedestrian detection Pedestrian Real time image pyramids Narrow band Texture Multiresolution analysis Multiple image Visual system Extrapolation Surveillance natural image statistics real-time systems Object detection Fine grain structure Natural scenes Passband
ISSN:	0162-8828, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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