Toward analyzing mutual interference on infrared-enabled depth cameras

摘要

Camera setups with multiple devices are a key aspect of ambient monitoring applications. These types of setups can result in data corruption when applied to recent RGB-D camera models because of mutual interference of the infrared light emitters employed by such devices. Consequently, the behavior of such interference must be appropriately evaluated to provide data that will allow monitoring systems to handle possible errors introduced into the data captured by depth sensors. However, multi-device setups have been explored in few studies in the current literature, especially in terms of the detailed measurements of the interference’s effect during long-term usage of RGB-D cameras. In this context, a methodology to evaluate the effect of mutual interference on the accuracy and precision of measured depth values is proposedin this article. The results of a series of experiments with different setups based on multiple depth cameras are explored. These setups include three devices that were widely used in studies in the computer vision literature related to depth imaging: theMicrosoft Kinect v2and twoIntel RealSensemodels:R200andD415. The experimental results indicate that theKinect v2yields considerably more stable depth readings than theRealSense R200in single-camera scenarios, even considering the influence of the warm-up time that is characteristic of time-of-flight devices such as theKinect v2. In multi-device setups, theKinect v2displays periodic peaks of mutual interference that increase in intensity depending on the distance between the cameras, with short-range setups yielding higher interference peaks. Further, the addition of more devices can potentially increase the duration of some interference peaks, albeit their intensity is not greatly affected. In long-range setups, the measured interference is small considering the experiments’ length, with the proportion of bad pixels among all captured frames ranging from 3.74% to 3.97% in a setup comprising three depth cameras. In turn, multi-device setups comprising theRealSensemodels are not affected by prejudicial interference peaks. In long-range setups, the instability of theR200leads to its results being less accurate and precise than those of theKinect v2under mutual interference. However, in close range multi-device setups, the high interference peaks observed with theKinect v2render theRealSensemodels a more stable alternative.