IMAGE BESTVISION Stuttgart VideosAMMJENACIONAL

Videos from the recent machine vision trade fair VISION Stuttgart are now available online.

Opening, Camera Technology, Robot Vision, Software & Deep Learning, Optics and Ilumination

3D, Hyperspectral imaging, Vision Processing, Camera Technology, Software & Deep Learning, Standards

Hyperspectral imaging, Camera Technology, Software and Deep Learning, Vision Processing, Optics and Illumination





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IMAGE BESTWill event-cameras dominate computer vision?AMMJENACIONAL

Dr. Ryad Benosman, a professor at University of Pittsburgh believes a huge shift is coming to how we capture and process images in computer vision applications. He predicts that event-based (or, more broadly, neuromorphic) vision sensors are going to dominate in the future. Dr. Benosman will be a keynote speaker at this year's Embedded Vision Summit .  EETimes published an interview with him; some excerpts below. According to Benosman, until the image sensing paradigm is no longer useful, it holds back innovation in alternative technologies. The effect has been prolonged by the development of high–performance processors such as GPUs which delay the need to look for alternative solutions. “Why are we using images for computer vision? That’s the million–dollar question to start with,” he said. “We have no reasons to use images, it’s just because there’s the momentum from history. Before even having cameras, images had momentum.” Benosman argues, image camera–based techniques for com...
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IMAGE BESTLow Light Video DenoisingAMMJENACIONAL

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A team from UC Berkeley and Intel Labs has posted a new pre-print titled "Dancing under the stars: video denoising in starlight". They present a new method for denoising videos captured in extremely low illumination of fractions of a lux. Abstract: Imaging in low light is extremely challenging due to low photon counts. Using sensitive CMOS cameras, it is currently possible to take videos at night under moonlight (0.05-0.3 lux illumination). In this paper, we demonstrate photorealistic video under starlight (no moon present, <0.001 lux) for the first time. To enable this, we develop a GAN-tuned physics-based noise model to more accurately represent camera noise at the lowest light levels. Using this noise model, we train a video denoiser using a combination of simulated noisy video clips and real noisy still images. We capture a 5-10 fps video dataset with significant motion at approximately 0.6-0.7 millilux with no active illumination. Comparing against  alternative method...
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IMAGE BESTProf. Eric Fossum's interview at LDV vision summit 2018AMMJENACIONAL

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Eric Fossum & Evan Nisselson Discussing The Evolution, Present & Future of Image Sensors Eric Fossum is the inventor of the CMOS image sensor “camera-on-a-chip” used in billions of cameras, from smartphones to web cameras to pill cameras and many other applications. He is a solid-state image sensor device physicist and engineer, and his career has included academic and government research, and entrepreneurial leadership. He is currently a Professor with the Thayer School of Engineering at Dartmouth in Hanover, New Hampshire where he teaches, performs research on the Quanta Image Sensor (QIS), and directs the School’s Ph.D. Innovation Program. Eric and Evan discussed the evolution of image sensors, challenges and future opportunities.     More about LDV vision summit 2022: https://www.ldv.co/visionsummit Organized by LDV Capital https://www.ldv.co/   [An earlier version of this post incorrectly mentioned this interview is from the 2022 summit. This was in fact fro...
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