Detail publikace

Object Tracking in Monochromatic Video Sequences Using Particle Filter

Originální název

Object Tracking in Monochromatic Video Sequences Using Particle Filter

Anglický název

Object Tracking in Monochromatic Video Sequences Using Particle Filter

Jazyk

en

Originální abstrakt

In recent years, a significant amount of attention has been given to the development of efficient and robust visual tracking algorithms. In order to deal with this problematic issue, color based particle filters are often used because of their simplicity, flexibility, and ability to deal with non-linearity and non-Gaussianity of such systems. However, the conventional particle filter methods may perform poorly when the color information is not available. In this paper, the proposed combination of a background model, motion model, and object model aims to tackle the problem of tracking objects in monochromatic video sequences. Several experiments have been conducted to verify the presented approach.   

Anglický abstrakt

In recent years, a significant amount of attention has been given to the development of efficient and robust visual tracking algorithms. In order to deal with this problematic issue, color based particle filters are often used because of their simplicity, flexibility, and ability to deal with non-linearity and non-Gaussianity of such systems. However, the conventional particle filter methods may perform poorly when the color information is not available. In this paper, the proposed combination of a background model, motion model, and object model aims to tackle the problem of tracking objects in monochromatic video sequences. Several experiments have been conducted to verify the presented approach.   

BibTex


@inproceedings{BUT96943,
  author="David {Herman} and Filip {Orság} and Martin {Drahanský}",
  title="Object Tracking in Monochromatic Video Sequences Using Particle Filter",
  annote="In recent years, a significant amount of attention has been given to the
development of efficient and robust visual tracking algorithms. In order to deal
with this problematic issue, color based particle filters are often used because
of their simplicity, flexibility, and ability to deal with non-linearity and
non-Gaussianity of such systems. However, the conventional particle filter
methods may perform poorly when the color information is not available. In this
paper, the proposed combination of a background model, motion model, and object
model aims to tackle the problem of tracking objects in monochromatic video
sequences. Several experiments have been conducted to verify the presented
approach.   ",
  address="Karel Englis College Inc.",
  booktitle="7th Scientific International Conference - Enviromental Protection of Population",
  chapter="96943",
  edition="NEUVEDEN",
  howpublished="print",
  institution="Karel Englis College Inc.",
  year="2012",
  month="may",
  pages="120--128",
  publisher="Karel Englis College Inc.",
  type="conference paper"
}