Performance evaluation of FIR sensor systems applied to pedestrian detection

Besides resolution, an important performance parameter of a FIR camera is the sensitivity. It depends on the sensitivity of the detector array itself and the characteristics of the optic. The effects of the optic are considerably driven by the f-number, with high values resulting in decreased sensitivity, but providing the possibility for simple lens design and cheaper production costs. In this contribution 4 different sensor setups with different optics are evaluated for their impact on the performance of trained pedestrian classifiers. To overcome the expensive and time consuming process of ground truth generation for multiple sensors, an approach for reusing available high sensitivity reference data is presented. Classifiers are trained on specially transformed reference data with characteristics of sensors with degraded sensitivity. For the evaluation of the classifiers, data of real world road scenarios is collected simultaneously with the target sensors mounted in parallel in a test vehicle, following a detailed script for recording a pedestrian scene test catalogue. This allows for a direct analysis and comparison of the different sensors and their impact on the detection performance