TY - JOUR
T1 - Optimization of ISP parameters for Object Detection algorithms
AU - Yahiaoui, Lucie
AU - Hughes, Ciarán
AU - Horgan, Jonathan
AU - Deegan, Brian
AU - Denny, Patrick
AU - Yogamani, Senthil
N1 - Publisher Copyright:
© 2019, Society for Imaging Science and Technology
PY - 2019/1/13
Y1 - 2019/1/13
N2 - In autonomous driving applications, cameras are a vital sensor as they can provide structural, semantic and navigational information about the environment of the vehicle. While image quality is a concept well understood for human viewing applications, its definition for computer vision is not well defined. This gives rise to the fact that, for systems in which human viewing and computer vision are both outputs of one video stream, historically the subjective experience for human viewing dominates over computer vision performance when it comes to tuning the image signal processor. However, the rise in prominence of autonomous driving and computer vision brings to the fore research in the area of the impact of image quality in camera-based applications. In this paper, we provide results quantifying the accuracy impact of sharpening and contrast on two image feature registration algorithms and pedestrian detection. We obtain encouraging results to illustrate the merits of tuning image signal processor parameters for vision algorithms.
AB - In autonomous driving applications, cameras are a vital sensor as they can provide structural, semantic and navigational information about the environment of the vehicle. While image quality is a concept well understood for human viewing applications, its definition for computer vision is not well defined. This gives rise to the fact that, for systems in which human viewing and computer vision are both outputs of one video stream, historically the subjective experience for human viewing dominates over computer vision performance when it comes to tuning the image signal processor. However, the rise in prominence of autonomous driving and computer vision brings to the fore research in the area of the impact of image quality in camera-based applications. In this paper, we provide results quantifying the accuracy impact of sharpening and contrast on two image feature registration algorithms and pedestrian detection. We obtain encouraging results to illustrate the merits of tuning image signal processor parameters for vision algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85075471694&partnerID=8YFLogxK
U2 - 10.2352/ISSN.2470-1173.2019.15.AVM-044
DO - 10.2352/ISSN.2470-1173.2019.15.AVM-044
M3 - Conference article
AN - SCOPUS:85075471694
SN - 2470-1173
VL - 2019
JO - IS and T International Symposium on Electronic Imaging Science and Technology
JF - IS and T International Symposium on Electronic Imaging Science and Technology
IS - 15
M1 - AVM-044
T2 - 2019 Autonomous Vehicles and Machines Conference, AVM 2019
Y2 - 13 January 2019 through 17 January 2019
ER -