The use of low-cost cameras for medical applications has its advantages as it enables affordable and remote evaluations of health problems; however, the accuracy is a limiting factor to use them. Previous studies indicate that parameters from object position like distance camera-object and angle of view could be used to improve temperature estimation from thermal cameras. Nevertheless, most studies are focused on expensive thermal cameras with good accuracy. In this study, an innovative experimental setup is used to study the errors associated to temperature estimation from a low-cost infrared camera: FlirOne Gen3. In our experiments, the image acquisition is done from multiple point of view (distance camera-object and viewing angles) and by using a thermal camera manipulated by hand. Then, using a regression model, a correction is proposed and tested. The results show that our proposed correction improves the temperature estimation and enhance the thermal accuracy.