Planar Segment Based Three‐dimensional Point Cloud Registration in Outdoor Environments

We present an odometry‐free three‐dimensional (3D) point cloud registration strategy for outdoor environments based on area attributed planar patches. The approach is split into three steps. The first step is to segment each point cloud into planar segments, utilizing a cached‐octree region growing algorithm, which does not require the 2.5D image‐like structure of organized point clouds. The second step is to calculate the area of each segment based on small local faces inspired by the idea of surface integrals. The third step is to find segment correspondences between overlapping point clouds using a search algorithm, and compute the transformation from determined correspondences. The transformation is searched globally so as to maximize a spherical correlation‐like metric by enumerating solutions derived from potential segment correspondences. The novelty of this step is that only the area and plane parameters of each segment are employed, and no prior pose estimation from other sensors is required. Four datasets have been used to evaluate the proposed approach, three of which are publicly available and one that stems from our custom‐built platform. Based on these datasets, the following evaluations have been done: segmentation speed benchmarking, segment area calculation accuracy and speed benchmarking, processing data acquired by scanners with different fields of view, comparison with the iterative closest point algorithm, robustness with respect to occlusions and partial observations, and registration accuracy compared to ground truth. Experimental results confirm that the approach offers an alternative to state‐of‐the‐art algorithms in plane‐rich environments.     

Processing and interactive editing of huge point clouds from 3D scanners

This paper describes a new out-of-core multi-resolution data structure for real-time visualization, interactive editing and externally efficient processing of large point clouds. We describe an editing system that makes use of the novel data structure to provide interactive editing and preprocessing tools for large scanner data sets. Using the new data structure, we provide a complete tool chain for 3D scanner data processing, from data preprocessing and filtering to manual touch-up and real-time visualization. In particular, we describe an out-of-core outlier removal and bilateral geometry filtering algorithm, a toolset for interactive selection, painting, transformation, and filtering of huge out-of-core point-cloud data sets and a real-time rendering algorithm, which all use the same data structure as storage backend. The interactive tools work in real-time for small model modifications. For large scale editing operations, we employ a two-resolution approach where editing is planned in real-time and executed in an externally efficient offline computation afterwards. We evaluate our implementation on example data sets of sizes up to 63 GB, demonstrating that the proposed technique can be used effectively in real-world applications.     

Estimation of stream channel geometry in Idaho using GIS-derived watershed characteristics

This paper describes estimation of stream channel geometry with multiple regression analysis of GIS-derived watershed characteristics including drainage area, catchment-averaged precipitation, mean watershed slope, elevation, forest cover, percent area with slopes greater than 30 percent, and percent area with north-facing slopes greater than 30 percent. Results from this multivariate predictor method were compared to results from the traditional single-variable (drainage area) relationship for a sample of 98 unregulated and undiverted streams in Idaho. Root-mean-squared error (RMSE) was calculated for both multiple- and single-variable predictions for 100 independent, random subsamples of the dataset at each of four different subsample levels. The multiple-variable technique produced significantly lower RMSE for prediction of both stream width and depth when compared to the drainage area-only technique. In the best predictive equation, stream width depended positively on drainage area and mean watershed precipitation, and negatively on fraction of watershed consisting of north-facing slopes greater than 30%. Stream depth depended positively on drainage area and precipitation, and negatively on mean watershed elevation. Our results suggest that within a given physiographic province, multivariate analysis of readily available GIS-derived watershed variables can significantly improve estimates of stream width and depth for use in flow-routing software models.     

Recovery of chromium from tannery effluents using a redox–adsorption approach

Adsorption isotherms for sodium and trivalent chromium uptake from aqueous solutions onto Amberlite resin were prepared at 18°C. Adsorption of each cation followed the Langmuir model. The rate of uptake of each cation was found to be film diffusion controlled with sodium showing the most rapid uptake. In aqueous solutions containing both chromium and sodium as the only cationic species, it was found that with increasing initial concentration of sodium, the trivalent chromium uptake on the resin decreased substantially. To overcome this difficulty a four step redox–adsorption system has been developed for the removal of Cr³⁺ from tannery effluents. The first step comprises the oxidation of trivalent chromium to the hexavalent form using selected common oxidising agents. The liquid effluent is then passed through an Amberlite cation-exchange resin in step 2 where the sodium in the waste stream is completely removed. The anionic hexavalent form of chromium (Cr₂O) passes unaltered through the resin along with the waste stream. In the third stage the dichromate is reduced back to the trivalent cationic form which is subsequently removed from the waste stream by a second Amberlite ion-exchange bed in stage 4. Each step in this process is assessed in batch and flow mode using simulated and real tannery effluents.     

Building a speech recognition system with privacy identification information based on Google Voice for social robots

The Journal of Supercomputing - Currently, many smart speakers, even social robots, appear on the market to help people's lives become more convenient. Usually, people use smart speakers to...     

High Figure of Merit (FOM) of Bragg Modes in Au‐Coated Nanodisk Arrays for Plasmonic Sensing

Gold‐coated nanodisk arrays of nearly micron periodicity are reported that have high figure of merit (FOM) and sensitivity necessary for plasmonic refractometric sensing, with the added benefit of suitability for surface‐enhanced Raman scattering (SERS), large‐scale microfabrication using standard photolithographic techniques and a simple instrumental setup. Gold nanodisk arrays are covered with a gold layer to excite the Bragg modes (BM), which are the propagative surface plasmons localized by the diffraction from the disk array. This generates surface‐guided modes, localized as standing waves, leading to highly confined fields confirmed by a mapping of the SERS intensity and numerical simulations with 3D finite element method. The optimal gold‐coated nanodisk arrays are applied for refractometric sensing in transmission spectroscopy with better performance than nanohole arrays and they are integrated to a 96‐well plate reader for detection of IgY proteins in the nanometer range in PBS. The potential for sensing in biofluids is assessed with IgG detection in 1:1 diluted urine. The structure exhibits a high FOM of up to 46, exceeding the FOM of structures supporting surface plasmon polaritons and comparable to more complex nanostructures, demonstrating that subwavelength features are not necessary for high‐performance plasmonic sensing.