![]() ![]() This enables us to deploy these tools for your projects so that you get the benefit of the latest in technology. OWorkers has forged a slew of partnerships with providers of the best tools for LIDAR annotation outsourcing. When you outsource LIDAR annotation, the partner that seeks to do this work for you should be able to demonstrate access to such tools and technologies. The annotation of LIDAR data, hence needs to be done through tools and technologies that are getting increasingly accurate and sophisticated. ![]() Besides, there will be the cost of continuing human effort. Human annotation of this data could take months and years and even decades, perhaps obviating its need by the time it gets completed. And each frame will need multiple annotations. For example, taking the oft-quoted example of an autonomous vehicle, if we decide that a minimum of a thousand kilometers worth of training data is required to train our model so that it becomes independent, it means that the set of frames that correspond to the journey will run into millions. The data generated by LIDAR is voluminous. What do we need to look for when we look for a partner to outsource LIDAR annotation to for our business? Modern and relevant Tools and Technologies are deployed That being said, as an outsourcer, you must be conscious of the benefits such an arrangement could deliver to your business, so that you specifically evaluate potential partners on the basis of those expectations. ![]() Outsourcing LIDAR annotation is now a well-accepted practice. Benefits you should expect when you outsource LIDAR annotation LIDAR annotation outsourcing identify objects in the ‘point cloud’ created by LIDAR and annotate it based on the requirement of the project, using one of the several annotation techniques available, like Bounding Boxes (or Bounding Cuboids since we are dealing with a 3D image), Semantic Segmentation or Polygons. ![]() What LIDAR annotation does is to assign meaning to the 3D images created with the help of LIDAR technology in a language that can be understood by a software program through its ‘computer vision.’ So, where does LIDAR annotation come into the picture? If you see a camera mounted on an autonomous vehicle, you are probably witnessing LIDAR at work. LIDAR does it faster and with great accuracy.Īutonomous Vehicles – Everyone’s favorite AI example, also depends on LIDAR for creation of high-resolution images based on which the vehicle identifies objects and navigates its way around them. It helps in reconstruction of models without having to assemble them piece by piece and also running the risk of damaging artefacts. Think town planning.Įnvironment and Conservation – LIDAR provides aerial 3D views of the Earth’s surface based on which scientists can estimate land-use patterns and change over a period of time to estimate, for instance, deforestation.Īrchaeology – Again, a logical application for LIDAR. Surveys – Compared to traditional surveys done manually, LIDAR surveys can be done rapidly and much more accurately. Though the future cannot be seen, LIDAR has already proved invaluable in many applications and is expected to become an even more integral contributor to the automation we will experience in our daily lives in the days to come.Īugmented Reality – LIDAR enables 3D mapping, enabling other systems to create data based on the high-resolution map created. Light Detection and Ranging is a remote sensing and surveying technology that emits a pulsed laser that travels to an object and back to the emission point, creating a three-dimensional image as a set of dots or points based on the time taken for the light to travel as well as the angle of the reflection. LIDAR is an acronym for Light Detection and Ranging. Before we discuss LIDAR annotation, let us spend a few minutes understanding LIDAR. ![]()
0 Comments
Leave a Reply. |