Noise Modelling and Uncertainty Propagation for TOF Sensors
نویسندگان
چکیده
Time-of-Flight (TOF) cameras are active real time depth sensors. One issue of TOF sensors is measurement noise. In this paper, we present a method for providing the uncertainty associated to 3D TOF measurements based on noise modelling. Measurement uncertainty is the combination of pixel detection error and sensor noise. First, a detailed noise characterization is presented. Then, a continuous model which gives the noise’s standard deviation for each depth-pixel is proposed. Finally, a closed-form approximation of 3D uncertainty from 2D pixel detection error is presented. An applicative example is provided that shows the use of our 3D uncertainty modelling on real data.
منابع مشابه
Noise Modeling in TOF Sensors with Application to Depth Noise Removal and Uncertainty Estimation in 3D Measurement
Time-Of-Flight (TOF) sensors provide real time depth information at high frame-rates. One issue with TOF sensors is the usually high level of noise (i.e. the depth measure’s repeatability within a static setting). However, until now, TOF sensors’ noise has not been well studied. We show that the commonly agreed hypothesis that noise depends only on the amplitude information is not valid in prac...
متن کاملSpatial modelling of railway noise propagation
In recent decades, population growth and progress of technology have shaped large and compact urban settlements. Existence of huge transportation systems and developed urban infrastructures are among the most important properties of modern cities. In spite of prompt transit and facilitated daily activities, development of transportation systems causes many problems, including traffic, air and n...
متن کاملModelling and Compensation of uncertain time-delays in networked control systems with plant uncertainty using an Improved RMPC Method
Control systems with digital communication between sensors, controllers and actuators are called as Networked Control Systems (NCSs). In general, NCSs encounter with some problems such as packet dropouts and network induced delays. When plant uncertainty is added to the aforementioned problems, the design of the robust controller that is able to guarantee the stability, becomes more complex. In...
متن کاملRobust Identification of Smart Foam Using Set Mem-bership Estimation in A Model Error Modeling Frame-work
The aim of this paper is robust identification of smart foam, as an electroacoustic transducer, considering unmodeled dynamics due to nonlinearities in behaviour at low frequencies and measurement noise at high frequencies as existent uncertainties. Set membership estimation combined with model error modelling technique is used where the approach is based on worst case scenario with unknown but...
متن کاملA Robust Feedforward Active Noise Control System with a Variable Step-Size FxLMS Algorithm: Designing a New Online Secondary Path Modelling Method
Several approaches have been introduced in literature for active noise control (ANC)systems. Since Filtered-x-Least Mean Square (FxLMS) algorithm appears to be the best choice as acontroller filter. Researchers tend to improve performance of ANC systems by enhancing andmodifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANCapplications an online secondary pat...
متن کامل