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WP2 status report

WP2 status report. G. Aielli Edusafe Spring School 07/03/2014. Fast real time video transmission. A solution has been found, sufficient for the EDUSAFE task: PARALINX ARROW system

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WP2 status report

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  1. WP2 status report G. Aielli Edusafe Spring School 07/03/2014

  2. Fast real time video transmission • A solution has been found, sufficient for the EDUSAFE task: PARALINX ARROW system • Commercial solution developed for video broadcasting in the movie maker field: the mobile cameras on open field scene are equipped with transmitters sending the images to the director supervisory post. The EDUSAFE application is of the same type… • Technically is a HDMI cable wireless extender • It works with a custom protocol over the 5.1-5.8 GHz radio base • It guarantee 1mS latency for delivering uncompressed audio/video in full HD • Tested in ATLAS successfully transmitter HDMI in receiver HDMI out • Purchased a TX/RX set + an double input HDMI frame grabber board (xPCI) to make extensive quality test • For the final system we propose an HDMI Gbit Ethernet converter to be able to deliver the image to a remote server over optical fiber

  3. EDUSAFE AR final architecture SERVER 2 Head mounted Data acquisition 1 EDGE detection (Roma) Video / audio (Noca) 1-1 2-1 1-3 2.2 WRM (Roma) RT WiFiTx Full HD image 2.7 FeaturesDatabase (EPFL) 2.8 WRM FeatureDatabase (Roma) Parameter space RT WiFi Rx Inertial sensors (Noca) 1-4 Full Color Image IMU data 2D object detection + 3D pose determination (EPFL) 3.2 & 3.3 Color Image Standard WiFi+ Router 2.6 2D objectdetection (EPFL) Pose data 3D pose determination (EPFL) Interface protocol (Noca) RT WiFiTx RT WiFi Rx 3.2 Adv. Pose data 3.3 Basic Pose data 3.1 IMU data Supervision Sensors (Prisma) 3.5 Compressed image Sensor Fusion (CERN) PTU 3 Supervision / Control and DAQ system (IASA) 2.3 3.4 3.6 WIFI module Transmission protocols (Noca) Fused pose data Supervision exchange AR Content Visualization SW (CERN) 2D /3D objects proceduresDatabase (CERN) 4 2.5 HMD Display Hardware (TUM) 4.1 User interface (TUM+CERN) 4.2 Eye Tracking (TUM) 4.3 5 Gamma Imaging camera and algorithm (Canberra) 2.4 Authoring tool (CERN)

  4. Impact on the architecture Video sensor source receiver server • The audio/video source will be available on the server in real time: • Usable for supervision purposes due to smooth HQ images and sounds • WRM can be effectively inserted in the loop now • The visual tracking computing can be now replicated in parallel on the server without HW limitations • The tracking process on the PTU still has the advantage of no dependence on the wireless video stream  more reliable and absolutely needed • The sensor fusion process will have now up to 4 independent tracking sources to be combined: • IMU • Local PTU visual tracking • Replicated visual tracking on the server • WRM based visual tracking on the server • Further use of this transmitter possible toward the operator in case of need open discussion on further architecture options/simplifications Vis. Track. replica WRM Vis. Track. Exploiting WRM PTU IMU Vis. Track. Sensor fusion

  5. Roma EpflCern meeting WP2 related • Meeting focused on implementing the WRM in the AR system • New use case to avoid ATLAS schedule constraints  Olga • ROMA updates • Recent breakthrough in the WRM implementation: long segment tracking fully working !  open up the possibility of arbitrary shape detection at 3.3 Kframes /s -- 1Mpixel image (existing WRM)  Ali slides • Need a better edge detector that works well on color images collaboration with Vincent • 1 bulgarian engineer might be hired soon for the ER. • Critical implementation points for the project: • edge detector implementation • Overall cost for the test system 50 KCHF estimation partially covered with the column 3  proposed to point out all the HW EDUSAFE cost share within partners • Includes foundry test run, xPCI board design and construction, side electronics • Discussion of collaboration between EPFL and Roma • At the moment segment finding can not be used directly by EPFL software (still hopes ??). Open discussion on this point. Thinking of new techniques? • Part detection of EPFL is the slowest element of the SW of EPFL. Roma will pursue part detection by WRM. Warning this is a new challenge!

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