Detail publikace

Real-time Algorithms of Object Detection with Classifiers

Originální název

Real-time Algorithms of Object Detection with Classifiers

Anglický název

Real-time Algorithms of Object Detection with Classifiers

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

BibTex


@inbook{BUT91467,
  author="Roman {Juránek} and Michal {Hradiš} and Pavel {Zemčík}",
  title="Real-time Algorithms of Object Detection with Classifiers",
  annote="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.",
  address="InTech - Open Access Publisher",
  booktitle="Real-Time System",
  chapter="91467",
  edition="NEUVEDEN",
  howpublished="print",
  institution="InTech - Open Access Publisher",
  year="2012",
  month="march",
  pages="1--22",
  publisher="InTech - Open Access Publisher",
  type="book chapter"
}