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JURÁNEK, R. HRADIŠ, M. ZEMČÍK, P.
Original Title
Real-time Algorithms of Object Detection with Classifiers
Type
book chapter
Language
English
Original Abstract
Real-time object detection is currently expanding field of computer vision. One of most popular methods for the object detection is based on exploitation of statistical classifiers (namely those based on AdaBoost algorithm). This contribution presents methods for acceleration of object detection based on the AdaBoost. First it describes image pre-processing and the learning of classifiers. Finally, the contribution presents algorithmic accelerations of the detection process and effective implementations of classification on various architectures - CPU/SSE, GPGPU and FPGA. Accelerated detectors achieve high performance compared to state of the art solutions and are suitable for real-time applications.
Keywords
WaldBoost, Object Detection, Classification Cost, EnMS, Neighborhood Suppression, Acceleration, GPU, SIMD, FPGA
Authors
JURÁNEK, R.; HRADIŠ, M.; ZEMČÍK, P.
RIV year
2012
Released
24. 3. 2012
Publisher
InTech - Open Access Publisher
Location
Rijeka
ISBN
9789535105107
Book
Real-Time System
Pages from
1
Pages to
22
Pages count
URL
http://www.intechopen.com/books/real-time-systems-architecture-scheduling-and-application
BibTex
@inbook{BUT91467, author="Roman {Juránek} and Michal {Hradiš} and Pavel {Zemčík}", title="Real-time Algorithms of Object Detection with Classifiers", booktitle="Real-Time System", year="2012", publisher="InTech - Open Access Publisher", address="Rijeka", pages="1--22", isbn="9789535105107", url="http://www.intechopen.com/books/real-time-systems-architecture-scheduling-and-application" }