A breakthrough in our shared understanding, perception, and description of human body shape brings new alternatives to 3D body scanning
ANAHEIM, CALIFORNIA -- JULY 26, 2016 -- Researchers from the Max Planck Institute for Intelligent Systems and the University of Texas at Dallas, revealed new crowdshaping technology at SIGGRAPH 2016 that creates accurate 3D body models from 2D photos using crowdsourced linguistic descriptions of body shape. The Body Talk system takes a single photo and produces 3D body shapes that look like the person and are accurate enough to size clothing. It does this using the help of 15 volunteers who rate the body shape in the photo using 30 words or fewer. The researchers believe this technology has applications in online shopping, gaming, virtual reality and healthcare.
The FAUST dataset wins the "Dataset Award" at the Eurographics Symposium on Geometry Processing 2016. The award encourages and recognises the importance of the distribution of high-quality datasets on which geometry processing algorithms are tested.
A Nao flies East and helps Laura Sevilla to teach technology knowledge to children from the Philippines
Fascinated Kids with excited faces and curious voices, expressing happiness and thankfulness...- these emotions were raised by a little NAO robot that was the main actor of a robot workshop that took place in May 2015 in the Philippines. Laura Sevilla, a PostDoc at the MPI for Intelligent Systems in Tübingen, took two months off and volunteered more than five weeks in order to organize and lead this workshop.
Dr. Black recognized for his leadership in advancing body modeling and computer vision sciences
Body Labs (bodylabs.com), the provider of the world's most advanced technology for analyzing the human body's shape, pose and motion, announced today that Michael J. Black, Body Labs co-founder and board member, will be inducted as a foreign member of the Royal Swedish Academy of Sciences.
Cordelia Schmid, an Inria research director, has received the Humboldt Research Award for her work on computer vision spanning more than 20 years.
She was nominated for this scientific award by Michael Black, the director of the Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. As the director of the LEAR team and then the Thoth team since 1 January 2016, Cordelia Schmid is particularly interested in visual recognition linking invariant image descriptors with learning methods. Her research enables a computer to learn not only to interpret all types of real images and videos, but also to recognize objects, actions and places by learning large image and video bases containing more than 100 million images. Cordelia Schmid figures among the world’s precursors and leaders in the field of modern visual recognition methods; she is also named in the “Highly Cited Researchers 2015” list (source: Thomson Reuters).
Perception is essential for Intelligence
Einen Wagen mit Chauffeur könnte es irgendwann für jeden geben, wenn nämlich ein Roboter das Steuer übernimmt. Damit Autos auch ohne großen technischen Aufwand autonom fahren können, müssen Computer unübersichtliche Verkehrssituation jedoch mindestens genauso gut beurteilen wie der Mensch.
The 2015 PAMI Mark Everingham Prize was awarded to the Middlebury Dataset (Daniel Scharstein, Richard Szeliski, and team) for a series of datasets and on-line evaluations, starting with the Stereo datasets in 2001, and extending to Optical Flow, MRF and others, which have inspired many other datasets. Michael Black was part of the team behind the Optical Flow dataset and evaluation.
Ali Osman Ulusoy, Andreas Geiger and Michael Black receive the Best Paper Award at this years 3D Vision Conference for their paper "Towards Probabilistic Volumetric Reconstruction using Ray Potentials".