Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
The paper is devoted to empirical accuracy analysis of the visual localization problem. The accuracy is considered with attention to the design of a maintenance system for an industrial manufacturing cell. Three cases of localization are considered that constitute the most relevant acquisition conditions: single view, dual view, and partial occlusions. A virtual environment is developed for simulation in close to realistic conditions that allows one to account for feature point detection algorithms, camera resolution, etc. Important results have been obtained for the maintenance system design. The simulation revealed that the accuracy is strongly dependent on the distance to the target object and the number of visible points. The orientation error shows little dependence on the altitude of the camera relatively to the target object. The position error exhibits a clear minimum at a particular angle between the cameras in dual view observation. The accuracy under occlusions also indicates a number of patterns.
| Язык оригинала | английский |
|---|---|
| Название основной публикации | Proceedings - 2022 International Russian Automation Conference, RusAutoCon 2022 |
| Издатель | Institute of Electrical and Electronics Engineers Inc. |
| Страницы | 354-360 |
| Число страниц | 7 |
| ISBN (электронное издание) | 9781665466554 |
| DOI | |
| Состояние | Опубликовано - 4 сен 2022 |
| Опубликовано для внешнего пользования | Да |
| Событие | 2022 International Russian Automation Conference (RusAutoCon) - Sochi, Российская Федерация Продолжительность: 4 сен 2022 → 10 сен 2022 |
| Название | Proceedings - 2022 International Russian Automation Conference, RusAutoCon 2022 |
|---|
| конференция | 2022 International Russian Automation Conference (RusAutoCon) |
|---|---|
| Сокращенное название | RusAutoCon |
| Страна/Tерритория | Российская Федерация |
| Город | Sochi |
| Период | 4/09/22 → 10/09/22 |
ID: 99111417