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Reduced Search Space for Rapid Bicycle Detection

Författare

Summary, in English

This paper describes a solution to the application of rapid detection of bicycles in low resolution video. In

particular, the application addressed is from video recorded in a live environment. The future aim from the

results in this paper is to investigate a full year of video data. Hence, processing speed is of great concern.

The proposed solution involves the use of an object detector and a search space reduction method based on

prior knowledge regarding the application at hand. The method using prior knowledge utilizes random sample

consensus, and additional statistical analysis on detection outputs, in order to define a reduced search space. It

is experimentally shown that, in the application addressed, it is possible to reduce the full search space by 62%

with the proposed methodology. This approach, which employs a full detector in combination with the design

of a simple and fast model that can capture prior knowledge for a specific application, leads to a reduced search

space and thereby a significantly improved processing speed.

Avdelning/ar

Publiceringsår

2013

Språk

Engelska

Publikation/Tidskrift/Serie

[Host publication title missing]

Dokumenttyp

Konferensbidrag

Förlag

SciTePress

Ämne

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Nyckelord

  • Bicycle Detection
  • Search Space
  • RANSAC
  • SMQT
  • split up SNoW

Conference name

2nd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2013)

Conference date

2013-02-15 - 2013-02-18

Conference place

Barcelona, Spain

Status

Published

Forskningsgrupp

  • Mathematical Imaging Group