Exploring the potential of combining time of flight and thermal infrared cameras for person detection
This work addresses person detection in applications like surveillance or robotics by fusing sensor data, but it is incremental as it builds on existing sensor fusion concepts with specific adaptations.
The paper explores combining low-cost thermal infrared and time-of-flight range sensors for person detection, proposing a novel calibration approach that differs from stereo camera calibration due to spectral and resolution differences, and discusses methods to compensate for measurement errors to potentially increase accuracy and robustness with simpler algorithms.
Combining new, low-cost thermal infrared and time-of-flight range sensors provides new opportunities. In this position paper we explore the possibilities of combining these sensors and using their fused data for person detection. The proposed calibration approach for this sensor combination differs from the traditional stereo camera calibration in two fundamental ways. A first distinction is that the spectral sensitivity of the two sensors differs significantly. In fact, there is no sensitivity range overlap at all. A second distinction is that their resolution is typically very low, which requires special attention. We assume a situation in which the sensors' relative position is known, but their orientation is unknown. In addition, some of the typical measurement errors are discussed, and methods to compensate for them are proposed. We discuss how the fused data could allow increased accuracy and robustness without the need for complex algorithms requiring large amounts of computational power and training data.