Abstract
Time of Flight (ToF) sensors are the source of various errors, including the multi-camera interference artifact caused by the parallel scanning mode of the sensors. This paper presents the novel Importance Map Based Median filtration algorithm for interference artifacts suppression, as the potential 3D filtration method. The approach is based on the processing of multiple depth frames, using the extraction of the interference region and application of the interpolation. Considering the limitations and good functionalities of proposed algorithm, the combination with some standard methods was suggested. Performance of the algorithm was evaluated on the dataset consisting of the real-world objects with different texture and morphology against popular filtering methods based on neural networks and statistics.
Highlights
Due to the demand in the last decades, there are several types of depth cameras available on the market
The performance of the proposed algorithm was evaluated in comparison to known methods for point cloud filtering based on how precise they remove the interference artifacts
The scanning system demands several Time of Flight (ToF) cameras in its spatial topology, which results in the multi-camera interference error
Summary
Due to the demand in the last decades, there are several types of depth cameras available on the market. They use the different operation principles of depth sensors, that allow reconstructing the geometric properties of the environment. With the advantage of non-invasive nature and eye-safety of ToF cameras, medical research and imaging is the potential area of use. Besides all advantages, ToF cameras are subject to a large variety of measurement error sources. The number of investigations of these errors were reported and have shown that they are caused by sensor parameters and properties or environment configuration [2]. Essential ToF camera errors include multi-path (MPI) and multi-camera interference (MCI)
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