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Density-Based Vehicle Counting with Unsupervised Scale Selection

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU138878" target="_blank" >RIV/00216305:26230/20:PU138878 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.dicta2020.org/wp-content/uploads/2020/09/22_CameraReady.pdf" target="_blank" >http://www.dicta2020.org/wp-content/uploads/2020/09/22_CameraReady.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/DICTA51227.2020.9363401" target="_blank" >10.1109/DICTA51227.2020.9363401</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Density-Based Vehicle Counting with Unsupervised Scale Selection

  • Original language description

    A significant hurdle within any counting task is the variance in scale of the objects to be counted. While size changes of some extent can be induced by perspective distortion, more severe scale differences can easily occur, e.g. in case of images taken by a  drone from different elevations above the ground. The aim of our work is to overcome this issue by leveraging only lightweight dot annotations and a minimum level of training supervision. We propose a modification to the Stacked Hourglass network which enables the model to process multiple input scales and to automatically select the most suitable candidate using a quality score. We alter the training procedure to enable learning of the quality scores while avoiding their direct supervision, and thus without requiring any additional annotation effort. We evaluate our method on three standard datasets: PUCPR+, TRANCOS and CARPK. The obtained results are on par with current state-of-the-art methods while being more robust towards significant variations in input scale.

  • Czech name

  • Czech description

Classification

  • 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)

Result continuities

  • 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)

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Digital Image Computing: Techniques and Applications 2020

  • ISBN

    978-1-7281-9108-9

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    1-8

  • Publisher name

    Institute of Electrical and Electronics Engineers

  • Place of publication

    Melbourne

  • Event location

    Melbourne

  • Event date

    Nov 30, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000935148000034