Toward automated generation of parametric BIMs based on hybrid video and laser scanning data

Only very few constructed facilities today have a complete record of as-built information. Despite the growing use of Building Information Modelling and the improvement in as-built records, several more years will be required before guidelines that require as-built data modelling will be implemented for the majority of constructed facilities, and this will still not address the stock of existing buildings. A technical solution for scanning buildings and compiling Building Information Models is needed. However, this is a multidisciplinary problem, requiring expertise in scanning, computer vision and videogrammetry, machine learning, and parametric object modelling. This paper outlines the technical approach proposed by a consortium of researchers that has gathered to tackle the ambitious goal of automating as-built modelling as far as possible. The top level framework of the proposed solution is presented, and each process, input and output is explained, along with the steps needed to validate them. Preliminary experiments on the earlier stages (i.e. processes) of the framework proposed are conducted and results are shown; the work toward implementation of the remainder is ongoing.

Digital data transmission using electro-optically modulated vertical-cavity surface-emitting laser with saturable absorber

An electro-optically (EO) modulated oxide-confined vertical-cavity surface-emitting laser (VCSEL) containing a saturable absorber in the VCSEL cavity is studied. The device contains an EO modulator section that is resonant with the VCSEL cavity. A type-II EO superlattice medium is employed in the modulator section and shown to result in a strong negative EO effect in weak electric fields. Applying the reverse bias voltages to the EO section allows triggering of short pulses in the device. Digital data transmission (return-to-zero pseudo-random bit sequence, 27-1) at 10Gb/s at bit-error-rates well below 10-9 is demonstrated. © 2014 AIP Publishing LLC.

Detect the sub-wavelength data by applying a very-small-aperture laser

We present a theoretical and experimental research about applying a very-small-aperture laser (VSAL) to detect sub-wavelength data. Near-field distribution of a VSAL, which is essential for the application of such near-field devices, will be affected by the sample or fiber posited in the near-field region of the aperture. When the device is applied to detect the sub-wavelength data, the real resolution depends on the near-field spot size, the divergent angle of the beam and the distance from the aperture to the sample. Experimental results, including the near-field detection of the spot and detection of the sub-wavelength data by using the VSAL, are presented in this paper. We realize the two dimensional scanning about the sub-wavelength data (with the width 600 nm) by employing a VSAL with a 300 nm x 300 nm aperture.

Fast line, arc/circle and leg detection from laser scan data in a player driver

A feature detection system has been developed for real-time identification of lines, circles and people legs from laser range data. A new method sutable for arc/circle detection is proposed: the Inscribed Angle Variance (IAV). Lines are detected using a recursive line fitting method.

Building 3D City Models: Testing and Comparing Laser Scanning and Low-Cost UAV Data Using FOSS Technologies

Contém resumo

Use of fused airborne scanning laser altimetry and digital map data for urban flood modelling

Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, Digital Surface Models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub-metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. The paper describes the development of a LiDAR post-processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post-processing produces a Digital Terrain Model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially-distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR-derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ~1m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a 2D finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features such as buildings and roads as well as taller vegetation features such as trees and hedges. This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features.

Using airborne laser altimetry to improve river flood extents delineated from SAR data

Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data.

Characterising errors in airborne laser altimetry data to extract soil roughness

Airborne laser altimetry has the potential to make frequent detailed observations that are important for many aspects of studying land surface processes. However, the uncertainties inherent in airborne laser altimetry data have rarely been well measured. Uncertainty is often specified as generally as 20cm in elevation, and 40cm planimetric. To better constrain these uncertainties, we present an analysis of several datasets acquired specifically to study the temporal consistency of laser altimetry data, and thus assess its operational value. The error budget has three main components, each with a time regime. For measurements acquired less than 50ms apart, elevations have a local standard deviation in height of 3.5cm, enabling the local measurement of surface roughness of the order of 5cm. Points acquired seconds apart acquire an additional random error due to Differential Geographic Positioning System (DGPS) fluctuation. Measurements made up to an hour apart show an elevation drift of 7cm over a half hour. Over months, this drift gives rise to a random elevation offset between swathes, with an average of 6.4cm. The RMS planimetric error in point location was derived as 37.4cm. We conclude by considering the consequences of these uncertainties on the principle application of laser altimetry in the UK, intertidal zone monitoring.