A New Dimension of Vision through Point Clouds, Engineered by AI.
ABOUT LIDARIST
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Our Vision
“We aim to fully utilize the potential of point clouds among us by tailor-made algorithm, AI and state-of-art deep learning application.”
We believe LiDAR is the new perception, a perception allowing vision with real dimensions. Through LiDAR or point clouds, we see the world not only images but also arrays of data interpreting the dimensions of the world. In computer visions, we, Lidarist discover valuable data from point clouds; describe the world (objects) through point clouds; define the digital reflection of the real world. We foresee point clouds is becoming a power tool and media and we aim to fully utilize the potential of point clouds among us by tailor-made algorithm, AI and state-of-art deep learning application.
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Our Story
“We see ourself as Lidarist - specialist & scientist in LiDAR.”
We, Lidarist are in various expertise including building engineering, surveying, computer science and active scientist in LiDAR technology. Merging our expertise, we developed a robust solution to construction by using LiDAR and the point cloud data. Behind the equations and algorithm, more important, we are passionate people who aim to aspire a better future of the industries. We see ourself as Lidarist - specialist & scientist in LiDAR.
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Our Focus
“We are professional in point clouds and deep-learning.”
We are professional in point clouds and deep-learning. Our expertise tackle raw point clouds by AI-powered semantic segmentation and state-of-art deep learning application. Construction engineering is our first interest in which we provide solution for building components recognition and as-built BIM reconstruction. We have developed a complete workflow for "underground utilities point clouds to BIM approach". Through the future collaboration with UU shareholders, our unique neural network will be further evolved into a robust mind able to handle most of the scenario of underground utilities. Ultimately, our approach helps to construct the underground 3D map from point clouds.
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Our Approach
“We work from data acquisition to data extraction through our algorithm and machine learning approach.”
Data Acquisition:
We use different kind of terrestrial laser scanners including static and hand-held scanners for point cloud data acquisition in fitting different circumstance in buildings or construction sites and in suiting various output. If global positioning is required, the data will be transformed with geo-reference points either obtained by geosystem map or by GNSS RTK rover.
Data Extraction:
Through our algorithm and machine learning approach, we identify building components - walls, ceiling, floor, columns, ceiling tiles, air diffusers, recognize objects from the point cloud data. Further, we are developing a robust library and a neural network for fully automatic recognition of specific objects.
