Prediction of XYZ coordinates from an image using mono camera
| Autor: | Aris Nasuha, Fatchul Arifin, Yuniar Indrihapsari, Dessy Irmawati, Nur Hasanah, Muslikhin |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 1456:012015 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/1456/1/012015 |
| Popis: | Estimating the position of a homogeneous object from an image for XY position is quite simple because it has the same dimensions XY. However, determining the XYZ position requires a unique approach. Generally, for estimating 3D position, stereo camera or expensive cameras are used with complicated computer vision algorithms. In this paper, we classify the position of an object using a mono camera. The image is divided into 3185 classes and five layers as a machine learning algorithm references. The k-nearest neighbors (kNN) approach usually is to find the closest point of the centroids to the closest class. Thus, this approach can be used as a three-axis prediction method that can afford the best performance solution. |
| Databáze: | OpenAIRE |
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