Pedestrian Detection from Low Resolution Public Cameras in the Wild

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU127222" target="_blank" >RIV/00216305:26220/18:PU127222 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1109/SPIN.2018.8474255" target="_blank" >http://dx.doi.org/10.1109/SPIN.2018.8474255</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SPIN.2018.8474255" target="_blank" >10.1109/SPIN.2018.8474255</a>

Result language

angličtina

Original language name

Pedestrian Detection from Low Resolution Public Cameras in the Wild

Original language description

Since security situation in the world is changing, monitoring of protected areas using surveillance systems has been of increased significance in the recent years. Although the today object detection methods significantly improved accuracy, for real situations, where the video is stream basically of a low resolution and objects are often small and blurry, the methods are still struggling with precise detection. The key parts of any security system are 1) person detection and then also 2) person recognition, which must perform in real-time processing. This paper deals with pedestrian detection in so called wild - i.e. from sources with bad quality, blurry images or small objects for detection. We used Single Shot MultiBox Detector (SSD) which was trained on VOC 2007 dataset and using fine-tuning it achieved percentage increase 11.98% of accuracy for life scenarios. Thus, SSD confirmed its state-of-the-art position and ability to be simply adapted to specific cases of detection while keeping its high performance.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2018

Confidentiality

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

Article name in the collection

2018 5th International Conference on Signal Processing and Integrated Networks (SPIN)

ISBN

978-1-5386-3045-7

ISSN

—

e-ISSN

—

Number of pages

5

Pages from-to

291-295

Publisher name

Neuveden

Place of publication

New Delhi, India

Event location

Dept. of ECE, ASET, Amity University, Noida Sec-

Event date

Feb 22, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000446953700055