The rise of interest in Building Information Modelling (BIM) during the last years has led to the introduction of complex data structures. Among all this information, a precise definition of structures in the form of point clouds is still an open research area. Consequently, an accurate, fast and easy to use point cloud acquisition system is needed. In this paper, we present a hardware-software prototype for automated indoor environments scanning through the acquisition of point clouds using multiple low-cost depth sensors. The acquisition and processing phase are described in detail, as well as the test environments used to assess the system functionality.
2.5/3G devices should achieve satisfactory QoS, overcoming mobile standards drawbacks. In-service/blind quality monitoring is essential in order to improve perceptual quality according to Human Visual System. Several techniques have been proposed for image/video quality assessment. A novel no-reference quality index which uses an effective HVS model is proposed. Luminance masking, Contrast Sensitivity Function and temporal masking are taken into account with fast in-service algorithms. The proposed index is able to assess blockiness distortion with a fast image-domain measure. Compression/post-processing blurring effects are measured with a standard approach. Moving artifacts distortion is evaluated taking into account standard deviation with respect to a natural image statistical model. Several distortion effects, in wireless noisy channels with low video-streaming/playback bit rates (e.g. edge busyness and image persistence) are evaluated. A multi-level pooling algorithm (block, temporal-window, frame, and sequence levels) is used. Validation tests have been developed in order to assess index performance and computational complexity. The final measure provides human-like threshold-effect and high correlation with subjective data. Low complexity algorithms can be derived for real-time, HVS-based, QoS management for low-power consumer devices. Different distortion effects (e.g. ringing and jerkiness) can be easily included.
No-reference metrics are very useful for In-Service streaming applications. In this paper a blind measure for video quality assessment is presented. The proposed approach takes into account HVS Luminance Masking, Contrast Sensitivity and Temporal Masking. Video distortion level is then computed evaluating blockiness, blurring and moving artifacts. A global quality index is obtained using a multi-dimensional pooling algorithm (block, temporal window, frame, and sequence levels). Different video standard and several compression ratios have been used. A non-linear regression method has been derived, in order to obtain high linear and rank order correlation factors between human observer ratings and the proposed HVS-based index. Validation tests have been developed to assess index performance and computational complexity. Experimental results show that high correlation factors are obtained using the HVS models.
Many multimedia applications deal with image progressive transmission in order to reduce channel bandwidth and to allow for interactivity between users and service providers. In this framework, the paper presents a novel two-source coding scheme where thumbnail data are interpolated by fractal zooming to obtain higher resolution images; the relevant residual information is then coded by vector quantizing the wavelet decomposition coefficients. Performance of this novel scheme is evaluated on a variety of pictures, confirming its validity both in quantitative and qualitative terms (absence of block distortion).
In this paper, we design a new system for the transmission of multimedia information within the digital TV channel in a broadcast fashion. The scheme proposed is based on some DSM- CC functions, studying an additional syntax that allows us to convey all the data required to manage with the multimedia information at the reception side. The transport structure used is the well-known MPEG-2 Transport Stream, that is the most widespread platform for new digital television systems. The multimedia information conveyed in such a model is similar to that of the WWW system, that is an hypertextual file system where the text is integrated with images, sounds and animation. A proper encoding software has been realized, that codes the file system by means of the DSM-CC operations and brings out a transport stream.
A new interpolation algorithm for 2D data is presented that is based on the least-squares minimization and the use of splines. This interpolation technique is then integrated into a double source decomposition scheme for image data compression. First, a least-squares interpolation is implemented and applied to a uniform sampling image. Second, the splines and the analysis of the entropy allow us to reconstruct the final image. Experimental results show that the proposed image interpolation algorithm is very efficient. The major advantages of this new method over traditional block-coding techniques are the absence of the tiling effect and a more effective exploitation of interblock correlation.
The paper addresses the problem of reducing the computational load in block-based motion estimation (BBME) by exploiting a preliminary motion field, which is obtained from the coarsest level of a multiresolution pyramid, and its successive refinements in the finer ones. The first estimation is achieved by a full search, even on greatly reduced scales, whereas at the other levels just a small correction is computed, thereby achieving a speed increase. However, this results also in difficulty to improve an inaccurate initial estimation. The algorithm proposed in the paper overcomes such a drawback and even outperforms BBME in terms of rate vs. distortion through the computing of a variable-resolution motion field which allows the same reconstruction quality with fewer vectors. A good correction of wrong initial estimates is achieved by use of an appropriate propagation of displacement vectors from one level to the next one and of an adaptive search range. The vectors propagation is carried out by choosing the best vector among a set of neighbors taken from the previous level and among the already refined ones in the current level. The search range is chosen on the basis of the error in reconstructing the block related to the propagated vector. Finally, the adaptive resolution of the field is achieved by ending the propagation at an intermediate level of resolution, if a vector allows a good reconstruction quality of its block.
KEYWORDS: Superposition, Image compression, Visualization, Computer programming, Video compression, Reconstruction algorithms, Algorithm development, Video coding, 3D image processing, 3D video compression
A novel approach to video coding at very low bitrates is presented, which differs significantly from most of previous approaches, as it uses a spline-like interpolation scheme in a spatiotemporal domain. This operator is applied to a non-uniform 3D grid (built on sets of consecutive frames) so as to allocate the information adaptively. The proposed method allows a full exploitation of intra/inter-frame correlations and a good objective and visual quality of the reconstructed sequence.
Keywords: image processing; trilinear interpolation; 3D splitting; splines; adaptive approximation; image data compression; video coding.