Hierarchical Motion Tracking Using Matching of Sparse Features

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F18%3A00330726" target="_blank" >RIV/68407700:21240/18:00330726 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985807:_____/18:00497814

Výsledek na webu

<a href="http://dx.doi.org/10.1109/SITIS.2018.00075" target="_blank" >http://dx.doi.org/10.1109/SITIS.2018.00075</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SITIS.2018.00075" target="_blank" >10.1109/SITIS.2018.00075</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Hierarchical Motion Tracking Using Matching of Sparse Features

Popis výsledku v původním jazyce

Fundamental approaches in motion tracking are based on registration of pixel patches from one frame to another. To ensure invariance to some changes in the image and improve the speed of discovering a match, a pyramidal approach is used to steer the process faster to optima. However, registration of the patches in high resolution is still computationally expensive. Because we require the algorithm to process Ultra HD video content in real time on commonly available hardware, especially on mid-tier graphics processing units, approaches using matching of pixel patches are not feasible. In this paper, we present and evaluate an approach inspired by motion tracking on an image pyramid. However, instead of comparing pixel patches one to another, we utilise binary image descriptors that are much shorter and inherently use a Hamming distance for their direct comparison. Evaluation of our implementation, which is available on GitHub, was carried out on the Multiple Object Tracking challenge dataset.

Název v anglickém jazyce

Hierarchical Motion Tracking Using Matching of Sparse Features

Popis výsledku anglicky

Fundamental approaches in motion tracking are based on registration of pixel patches from one frame to another. To ensure invariance to some changes in the image and improve the speed of discovering a match, a pyramidal approach is used to steer the process faster to optima. However, registration of the patches in high resolution is still computationally expensive. Because we require the algorithm to process Ultra HD video content in real time on commonly available hardware, especially on mid-tier graphics processing units, approaches using matching of pixel patches are not feasible. In this paper, we present and evaluate an approach inspired by motion tracking on an image pyramid. However, instead of comparing pixel patches one to another, we utilise binary image descriptors that are much shorter and inherently use a Hamming distance for their direct comparison. Evaluation of our implementation, which is available on GitHub, was carried out on the Multiple Object Tracking challenge dataset.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA18-18080S" target="_blank" >GA18-18080S: Objevování znalostí v datech o aktivitě člověka založené na fúzi</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)

ISBN

978-1-5386-9385-8

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

449-456

Název nakladatele

IEEE Computer Society

Místo vydání

Los Alamitos

Místo konání akce

Las Palmas de Gran Canaria

Datum konání akce

26. 11. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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