Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/15228
Título: Pearson's correlation coefficient: a more realistic threshold for applications on autonomous robotics
Palavras-chave: Pearson’s correlation
Mobile robots
Autonomous robotics
Correlação de Pearson
Robôs móveis
Robótica autónoma
Data do documento: 2014
Editor: David Publishing Company
Citação: MIRANDA NETO, A. de. Pearson's correlation coefficient: a more realistic threshold for applications on autonomous robotics. Computer Technology and Application, [S. l.], v. 5, p. 69-72, 2014.
Resumo: Many applications for control of autonomous platform are being developed and one important aspect is the excess of information, frequently redundant, that imposes a great computational cost in data processing. Taking into account the temporal coherence between consecutive frames, the PCC (Pearson’s Correlation Coefficient) was proposed and applied as: discarding criteria methodology, dynamic power management solution, environment observer method which selects automatically only the regions-of-interest; and taking place in the obstacle avoidance context, as a method for collision risk estimation for vehicles in dynamic and unknown environments. Even if the PCC is a great tool to help the autonomous or semi-autonomous navigation, distortions in the imaging system, pixel noise, slight variations in the object’s position relative to the camera, and other factors produce a false PCC threshold. Whereas there are homogeneous regions in the image, in order to obtain a more realistic Pearson’s correlation, we propose to use some prior known environment information.
URI: http://repositorio.ufla.br/jspui/handle/1/15228
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