News


Lidar creates 3D effects for Game of


Thrones Lidar technology from Teledyne Optech has helped create visual effects and 3D spatial data acquisition for HBO’s Game of Thrones. Led by Vektra of Croatia, a visual


effects team used Teledyne’s lidar system to create a detailed 3D representation of the old city of Dubrovnik, the model for the fictional city of King’s Landing. They generated 3D point clouds in the set using various lidar technologies, including Teledyne Optech’s Maverick mobile lidar system and Polaris fixed terrestrial scanner. The lidar point clouds were then colourised with digital camera imagery and image fusion software. Traditionally, lidar has been used


for mapping and in construction, civil engineering, mining and transportation. Lidar is now of particular interest in the film industry because of its ability to scan buildings, or even entire cities, in 3D, while maintaining a high level of detail and accuracy.


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Computer vision for seeing around corners presented at CVPR


esearchers at the Computer Vision and Pattern Recognition (CVPR) conference in Long Beach, California,


in June have presented two different computational methods that give cameras the ability to see around corners. A team from Carnegie Mellon University,


the University of Toronto and University College London showed a non-line-of-sight (NLOS) imaging technique able to compute millimetre- and micrometre-scale shapes of curved objects. Non-line-of-sight imaging aims to recover


occluded objects by analysing their indirect reflections on visible scene surfaces. Meanwhile, researchers from the University


of Montreal, Princeton University and Algolux were able to reconstruct high- quality images of traffic signs and other 3D objects taken by either smartphone or vehicle cameras. Te Carnegie Mellon University work was


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supported by the Defense Advanced Research Project Agency’s Reveal programme, which is developing NLOS capabilities. Te research received a best paper award at the CVPR conference. Ioannis Gkioulekas, an assistant professor


in Carnegie Mellon’s Robotics Institute, said: ‘Other NLOS researchers have already demonstrated NLOS imaging systems that can understand room-size scenes, or even extract information using only naturally occurring light. ‘We’re doing something that’s


complementary to those approaches – enabling NLOS systems to capture fine detail over a small area.’ Te Carnegie researchers used an ultrafast


laser to bounce light off a wall to illuminate a hidden object. By knowing when the laser fired pulses of light, the researchers could calculate the time the light took to reflect from the object, bounce off the wall on its return trip and reach a sensor. Previous attempts to use these time-of- flight calculations to reconstruct an image of


6 Imaging and Machine Vision Europe • August/September 2019


the object have depended on the brightness of the reflections. But in this study, Gkioulekas said the


researchers developed a new method based purely on the geometry of the object, which in turn enabled them to create an algorithm for measuring its curvature. Te researchers used an imaging system


that is effectively a lidar capable of sensing single particles of light to test the technique on glass and plastic objects. Tey also combined the technique with optical coherence tomography, to reconstruct images of a US quarter. In addition to seeing around corners, the


technique was effective at seeing through diffusing filters, such as thick paper. It has been demonstrated only at short distances – a metre at most. Te University of Montreal accomplished


its steady-state non-line-of-sight imaging technique using conventional CMOS camera sensors and a change in illumination method – a small change to a car’s headlights or a smartphone’s flash. Te research opens a path to practical


implementation, said research partner Algolux, which provides embedded soſtware. Algolux believes this technology can strengthen the ability of autonomous vehicles to navigate in difficult road scenarios, even when the view is blocked by obstructions or vehicles. Other potential uses include increased


security for video surveillance, as well as uses for smartphones, augmented reality and medical imaging.


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University of Montreal


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