PTS, PTX, PLY, PTG and E57 files can be exported directly. Our highly compressed binary DP format will also export stright into Autodesk ReCap (with free plugin), Trimble Realworks, AVEVA LFM, Veesus Arena4D, ClearEdge3D, and CloudCompare.
On smaller scale indoor projects, yes it can. The DPI-8 is ideally suited to capture tight and confined spaces, or smaller scenes with lots of geometry and shadowing. On larger scale projects it will not replace but can augment traditional 3D laser scanning work flows to capture areas where it is not practical to set up a scanner. For best accuracy we recommend using surveyed or scale-bar targets. The DPI-8 is not able to capture in sunlight however.
The main differences are that the software that drives the DPI-8, Phi.3D has been developed to work on tablets. No laptop or PC is required. Also, the DPI-8 Kit is designed for one-handed operation.
Another key difference is that the data registration is achieved in real time. With Phi.3D, you find out immediately if you've captured the data you set out to capture. We also provide real time feedback about the integrity of the data collected and calibrate each DPI-8 Kit thoroughly and individually for highest accuracy.
We believe the future of 3D data collection is with phones and tablets not laptops and PCs.
The question does not exactly apply to our technology. The DPI-8 Kit captures 320x240 points 30 times a second. Most these points do not end up in the point cloud but instead are used to refine an existing point cloud.
Short answer: Typical single-frame accuracy will be between 1mm (at close ranges) and 15mm (at long ranges).
Global typical scene accuracy will be between 0.2% and 1.2% of the measured distance, depending on a number of factors like use of targets, scanning range and environment temperature.
Long answer: The way the DPI-8 Kit (and the majority of other camera-based scanners) operates is significantly different to a Laser Scanner:
Due to the limited Field-Of-View of the depth camera, a dataset is stitched from many camera frames, all of which have different position and orientation in space.
Every frame has some small amount of error in the data and pose which will accumulate over the space of data collection. The more frames are stiched (spatially, not necessarily over time!) the more error will accumulate.
This is the way all self-tracking camera-based scanners operate.
A good part of the error can be removed by (automated, on-board) post-processing of the data, especially when there are loops in the data. However some error will always remain.
Therefore it is important to distinguish between local and global accuracy:
Local accuracy (measuring short distances in local parts of the scene) will always be high and comparable to a laser scanner.
Global accuracy (measuring long distances across different parts of the scene) will be lower due to error accumulation and is typically between 0.5% and 1.2% of the measured distance.
If high global accuracy is desired we recommend the use of surveyed targets which can be used to eliminate accumulated error and can drastically improve long-distance accuracy. Phi.3D has a special component in the software to do this automatically during global optimization of the data.
If no survey-equipment is available but global accuracy is still important we recommend using measured distances between targets. These can be supplied to the system and act as a corrective constraint during global optimization of the data.
When using the native .DP file format (which is heavily compressed) you will be able to store around 1000 to 2000 datasets of typical size on the tablet.
The maximum size of each individual dataset is limited by on-device working memory (RAM). The Phi.3D software will provide visual feedback about how much of this limit is reached during collection. Typical maximum scene sizes are between one and two medium-sized rooms, depending on operating range and level of detail captured.
It should be noted that during capture, the way the data size increases is over screen content covered and not over time. For example: Scanning lots of surface area from a distance will increase scene size as well as scanning detail from short distance.
On the extreme ends this means that a scene will still be very small even if a user scans just one particular spot for a very long time. On the opposite this also means that scanning large areas very quickly will not reduce data size and typically only result in high noise levels and low accuracy which is undesirable.
When scanning from close distances more scene size will be occupied than capturing from large distances due to the higher level of detail captured.