Joint denoising and interpolation of depth maps for MS Kinect sensors

ABSTRACT Infrared structured light sensors are widely employed for control applications, gaming, acquisition of dynamic and static 3D scenes. Recent developments have lead to the availability on the market of low-cost sensors which prove to be extremely sensitive to noise, light conditions, materials, the surface nature of the objects, and their distance from the camera. As a matter of fact, accurate denoising and interpolation strategies are needed. The paper presents a quality enhancement strategy for depth maps targeting low-cost IR structured light sensors. The approach has been tested using the MS Xbox Kinect device in both indoor and outdoor scenarios under different light conditions

Three-Dimensional Motion Estimation of Objects for Video Coding

Three-dimensional (3-D) motion estimation is applied to the problem of motion compensation for video coding. We suppose that the video sequence consists of the perspective projections of a collection of rigid bodies which undergo a rototranslational motion. Motion compensation can be performed on the sequence once the shape of the objects and the motion parameters are determined. We show that the motion equations of a rigid body can be formulated as a nonlinear dynamic system whose state is represented by the motion parameters and by the scaled depths of the object feature points. An extended Kalman filter is used to estimate both the motion and the object shape parameters simultaneously. The inclusion of the shape parameters in the estimation procedure adds a set of constraints to the filter equations that appear to be essential for reliable motion estimation. Our experiments show that the proposed approach gives two advantages. First, the filter can give more reliable estimates in the presence of measurement noise in comparison with other motion estimators that separately compute motion and structure. Second, the filter can efficiently track abrupt motion changes. Moreover, the structure imposed by the model implies that the reconstructed motion is very natural as opposed to more common block-based schemes. Also, the parameterization of the model allows for a very efficient coding of the motion informatio

Statistical Based Motion Estimation for Video Coding

In this work, statistical based motion estimation is applied to the problem of motion estimation for video coding. We show that the motion equations of a rigid body can be formulated as a nonlinear dynamic system whose state is represented by the motion parameters and by the scaled depths of the object feature points. An extended Kalman filter is used to estimate the global motion, from which successive frames can be predicted in a motion compensated video coding system. The structure imposed by the model implies that the reconstructed motion is very natural in comparison to more common block-based schemes. Moreover, the parametrization of the model allows for a very efficient coding of motion informatio

An Object-Oriented Cognitive Source Coding Architecture for 3D Video Communications

Publication in the conference proceedings of EUSIPCO, Aalborg, Denmark, 201

On the realization of minimum noise and low-noise frequency sampling FIR filters

In this work the finite precision effects issue connected to the frequency sampling realization of FIR filters is considered. In particular, the performance of the frequency sampling filters is evaluated in terms of noise gain for the following three different realizations of the second-order elementary sections: the canonical direct form, the minimum roundoff noise structure, and the suboptimal state-space structure introduced by Bomar. An interesting property on the design of minimum noise second-order sections embedded in the frequency sampling structure, is given. The results obtained show that the realizations via minimum noise structures and Bomar's structures greatly outperform the realizations via canonical direct form structures, and, for very narrow-band filters, have noise gain comparable to that of nonrecursive direct realization