Time-of-flight range sensors have error characteristics which are complementary to passive stereo. They provide real time depth estimates in conditions where passive stereo does not work well, such as on white walls. In contrast, these sensors are noisy and often perform poorly on the textured scenes for which stereo excels. We explore their complementary characteristics and introduce a method for combining the results from both methods that achieve better depth accuracy than either alone. In our fusion framework, the depth probability distribution functions on depth from each of these sensor modalities are computed and then effectively merged. Robust and adaptive fusion is built on a pixel-wise reliability weighting function calculated for each method. In addition, since time-of-flight devices have primarily been used as individual sensors, they are typically poorly calibrated. We introduce a method that substantially improves upon the manufacturer's calibration. We demonstrate that our proposed techniques lead to improved accuracy and robustness on an extensive set of experimental results.


Sensor - Fusion power - Stereophonic sound - Physics - Nuclear