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Judgment panel

Important Dates

Submission of papersJanuary 19, 2018

Proposals for tutorials and workshopsJanuary 20, 2018

Notification of paper and proposals acceptanceFebruary 24, 2018

Submission of camera-readyMarch 10, 2018

Date of conferenceApril 10, 2018

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Keynote speaker

Dr. Reinhard Klette


School of Engineering, Computer and Mathematical Sciences Auckland University of Technology

Speech Title: Mono-, Bi-, or Tri-nocular Vision for Self-driving Cars

Abstract: Self-driving cars use various sensors, and different camera configurations contribute to the options for sensor configurations. The talk reports about currently obtained results (in joint work with CeRV researchers and PhD students) evaluating different camera configurations for two basic tasks for self-driving cars.

Visual odometry derives accurate position data for a moving vehicle based on recorded video data. The use of different camera configurations, and of different analysis strategies (as being possible by the used camera configuration) define particular techniques for visual odometry. A quantitative comparison is provided using KITTI test data.

Stixels are a mid-level representation of 3D data in traffic scenes (made famous by vision-based car control systems designed at Daimler A.G.). Stixels help to derive semantic segmentations of traffic scenes, which is a requirement for self-driving cars.  Stixels are commonly calculated based on binocular stereo vision. The talk informs about the use of a trinocular approach for increased accuracy, also quantitatively evaluated on KITTI test data.

Research at CeRV also applies deep learning for solving various object detection, tracking, or scene analysis tasks. However, the use of mathematically defined models appears to be the adequate way for visual odometry and stixel calculation.



IEEE Digital Xplore

The Accepted papers only in IRANOPEN International Conference will be submitted for inclusion in IEEE Digital Xplore.

Read More ... Date: 2018/01/11

Conference Secretariat

Address : Islamic Azad University of Qazvin, Qazvin Branch, Iran

Telephone : 33665275 -028

Fax : 33675782 -028

Zip code : 3419915195

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