Publication detail

Implementing the Local Binary Patterns with SIMD Instructions of CPU

HEROUT, A. JURÁNEK, R. ZEMČÍK, P.

Original Title

Implementing the Local Binary Patterns with SIMD Instructions of CPU

English Title

Implementing the Local Binary Patterns with SIMD Instructions of CPU

Type

conference paper

Language

en

Original Abstract

Usage of statistical classifiers, namely AdaBoost and its modifications, is very common in object detection and pattern recognition. Performance of such classifiers strongly depends on low level features they use. This paper presents an experimental implementation of the Local Binary Patterns (LBP) that uses SIMD instructions for acceleration. The experiments shows that the proposed implementation is about six times faster than the plain C implementation (i.e. with no special optimizations) and superior to optimized implementations of features with similar descriptive power.

English abstract

Usage of statistical classifiers, namely AdaBoost and its modifications, is very common in object detection and pattern recognition. Performance of such classifiers strongly depends on low level features they use. This paper presents an experimental implementation of the Local Binary Patterns (LBP) that uses SIMD instructions for acceleration. The experiments shows that the proposed implementation is about six times faster than the plain C implementation (i.e. with no special optimizations) and superior to optimized implementations of features with similar descriptive power.

Keywords

LBP, AdaBoost, Object Detection, Feature Extraction, SIMD, SSE, CUDA

RIV year

2010

Released

22.04.2010

Publisher

University of West Bohemia in Pilsen

Location

Plzeň

ISBN

978-80-86943-86-2

Book

Proceedings of WSCG 2010

Edition

NEUVEDEN

Edition number

NEUVEDEN

Pages from

39

Pages to

42

Pages count

4

URL

Documents

BibTex


@inproceedings{BUT34653,
  author="Adam {Herout} and Roman {Juránek} and Pavel {Zemčík}",
  title="Implementing the Local Binary Patterns with SIMD Instructions of CPU",
  annote="Usage of statistical classifiers, namely AdaBoost and its modifications, is very
common in object detection and pattern recognition. Performance of such
classifiers strongly depends on low level features they use. This paper presents
an experimental implementation of the Local Binary Patterns (LBP) that uses SIMD
instructions for acceleration. The experiments shows that the proposed
implementation is about six times faster than the plain C implementation (i.e.
with no special optimizations) and superior to optimized implementations of
features with similar descriptive power.",
  address="University of West Bohemia in Pilsen",
  booktitle="Proceedings of WSCG 2010",
  chapter="34653",
  edition="NEUVEDEN",
  howpublished="print",
  institution="University of West Bohemia in Pilsen",
  year="2010",
  month="april",
  pages="39--42",
  publisher="University of West Bohemia in Pilsen",
  type="conference paper"
}