Compairing human and machine detection thresholds

Lezama, José - Blusseau, Samy - Randall, Gregory - Morel, Jean-Michel - Grompone von Gioi, Rafael

Resumen:

The mathematical theory of a contrario detection formalizes the non-accidentalness principle and attempts to predict ideal perception thresholds. Thus, it is natural to reconsider from a computational perspective, classic and new psychophysical experiments evaluating the human perception performance. To this aim, we chose the psychophysical experiments by Wagemans et al. where subjects are presented with Gabor-rendered outlines of real world objects. In these experiments, orientation jitter was added to the elements with the aim of determining its effect on human object detection performance. Using the a contrario theory, the human detection thresholds can be compared rationally to the algorithmic ones. To allow a broader experimentation, we built an online web facility where users can perform object detection experiments, and compare their detection curves to the ones predicted analytically by the computational model.


Detalles Bibliográficos
2012
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/41129
Acceso abierto
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Resumen:
Sumario:The mathematical theory of a contrario detection formalizes the non-accidentalness principle and attempts to predict ideal perception thresholds. Thus, it is natural to reconsider from a computational perspective, classic and new psychophysical experiments evaluating the human perception performance. To this aim, we chose the psychophysical experiments by Wagemans et al. where subjects are presented with Gabor-rendered outlines of real world objects. In these experiments, orientation jitter was added to the elements with the aim of determining its effect on human object detection performance. Using the a contrario theory, the human detection thresholds can be compared rationally to the algorithmic ones. To allow a broader experimentation, we built an online web facility where users can perform object detection experiments, and compare their detection curves to the ones predicted analytically by the computational model.