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Description
  • 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.
  • 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. (en)
Title
  • Real-time Algorithms of Object Detection with Classifiers
  • Real-time Algorithms of Object Detection with Classifiers (en)
skos:prefLabel
  • Real-time Algorithms of Object Detection with Classifiers
  • Real-time Algorithms of Object Detection with Classifiers (en)
skos:notation
  • RIV/00216305:26230/12:PU98175!RIV13-MSM-26230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(7H10013), P(7H10014), P(ED1.1.00/02.0070), S, Z(MSM0021630528)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 164274
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/12:PU98175
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • WaldBoost, Object Detection, Classification Cost, EnMS, Neighborhood Suppression, Acceleration, GPU, SIMD, FPGA (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [579A96229E5F]
http://linked.open...i/riv/mistoVydani
  • Rijeka
http://linked.open...vEdiceCisloSvazku
  • NEUVEDEN
http://linked.open...i/riv/nazevZdroje
  • Real-Time System
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...v/pocetStranKnihy
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Juránek, Roman
  • Zemčík, Pavel
  • Hradiš, Michal
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • InTech - Open Access Publisher
https://schema.org/isbn
  • 9789535105107
http://localhost/t...ganizacniJednotka
  • 26230
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