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THE CHALLENGES OF IMAGE QUALITY IN THE RACE FOR AUTONOMOUS VEHICLES
- 2. 2 If you buy a car that does not have the hardware necessary for self driving, it is like you are buying a horse… Google is working on self-driving cars, and they seem to work. People are so bad at driving cars that computers don't have to be that good to be much better.
- 3. 3 Tesla: 8 Cameras Mobileye: 13 Cameras Waymo: 29 Cameras Tesla Semi Truck: 28 Cameras What are the challenges to Camera based AV’s ?
- 4. 4 Challenging condition: High Dynamic situation
- 5. Challenging condition: Light transition Frames before, during and after the transition 5 T = 0.22s Under exposed T = 1.2s Over exposed T = 1.7s Correct
- 6. Challenging conditions: LED lighting 6 Courtesy of IEEE-P2020 Committee
- 7. 7 They have to be a LOT better! If Autonomous vehicles are relying on images from cameras, to make driving decisions, those images need to be of the highest quality, at all times in all conditions! Remember this Quote: Google is working on self-driving cars, and they seem to work. People are so bad at driving cars that computers don't have to be that good to be much better. How can we get there? By Working together!
- 8. IEEE-P2020 8 IEEE-SA P2020 working group on automotive imaging has been preparing new standards and performance metrics (KPI’s) to reduce the ambiguity in measurement of image quality of human vision and computer vision based cameras vis-a-vis their intended purpose.
- 9. DXOMARK Image Labs - An international team, Led by experts in Imaging, Audio, Display & Battery Testing and Development Services 9 2200+ m2 office space 16 labs 100+ experts X4 In 3 years
- 10. The Kingmaker of Smartphone Cameras 10
- 11. Our history For more than 10 years, DXOMARK has been setting the industry's standards for image quality and working with all camera and smartphone vendors to spur them to innovate and develop products with optimized quality for the benefit of end users. 2003 Launch of Analyzer 2008 Launch of DXOMARK.COM with DSC testing 2012 Smartphone camera testing 2017 DXOMARK becomes an independent company 2016 100th Analyzer lab installed 2019 Smartphone selfie & Audio testing 2020 Smartphone Display & Wireless Speakers Testing 11 2021 Battery Testing 2022 Videoconferencing Security, Automotive, Drone, 360/VR cameras testing
- 12. Comprehensive protocol development adapted to the applications Applications Objective Tests LAB Perceptual Tests REAL-LIFE Use Cases WDR LED Flicker Night Vision Moving Object Flare Image Quality Evaluation report 12
- 13. In-cabin camera – human vision and DMS Portrait Color Timing Setup HDR Portrait Setup Face exposure convergence White Blance and Color stability Color fidelity Frame rate, shutter time, rolling shutter Face details preservation 13 Perceptual field tests HDR Face exposure Entropy on bright pannel HDR Face detail preservation Objective lab tests Spatial visual video noise Temporal visual video noise Exposure Detail preservation Noise Focus range Video visual noise chart DXOMARK Chart Focus range chart
- 14. Front facing camera evaluation 14 Perceptual field tests Objective lab tests
- 15. Services for camera development 15 Support in tuning phase Specifications for camera image quality Measurement services and full report delivery Camera benchmark
- 16. We Provide Measurement Tools and Services 16
- 17. T H A N K Y O U ! 24-26, quai Alphonse le Gallo - 92100 Boulogne-Billancourt - France www.dxomark.com
Editor's Notes
- Camera is the eye of an autonomous vehicle If a camera miss an information, no matter how good is the AI, it might affect the AV decision and impact safety If you choose to use camera, it must be as good as possible What are the challenges?
- High dynamic scene This is a typical scene No information in the bright part. If traffic light, obstacle after at the end of the tunnel, at this point, the car is totally unaware and blind Same thing when we enter the tunnel = dangerous
- Sudden light transition: Use case: when we enter a tunnel Scene recorded in one of our colleagues car >> when we did that, it created an unwanted emergency break on his adas system Issue with the adaptation of the auto exposure Image goes under exposed to over exposed before reaching a correct image
- More and more LED in automotive environment on cars, traffic lights, lightings. The LED lighting is not continuous but our eyes do not perceive the blinking The camera video acquisition is sampled, that cause this Flicker effect Car lighting can easily be confused with turning light, traffic light might not be detected at all in some frames >>> might lead autonomous vehicle to take the wrong decision = danger
- Point out OEMs, Tier one, Autonomous vehicle platform makers, Chipset, sensor makers The P2020 Committee goal is to define Camera Image Quality Standards, both human vision and Computer vision
- Who we are
- For several years now, we are considered as a reference in camera evaluation
- Protocol methodology A lot of different application for automotive camera from human vision to computer vision application (object detection, line detection, driver monitoring system…) Use case list for each application For each use case we have objective tests lab and perceptual test > this is how we establish a complete report
- This is a first example of a protocol we have developed for a specific application. Goal: - Monitor driver’s behaviors under any condition Perceptual field test (any lighting conditions, daylight, HDR, night) all skin tones Description of objective lab tests and metrics. Describe PTC with dynamic lightings and HDR portrait. It’s important to have a face in the lab setup to fit real use case.
- Other example: Front facing camera Need to visualize and detect object long distance Description of perceptual field tests and objective lab tests. Emphasize on Collimator + P2020 metrics: Flicker, Flare, Noise, Dynamic range
- We can work in all the camera development phase. We can help OEM’s give specifications to their suppliers We can help camera makers in their optimization phase We can benchmark cameras for specific applications.