David Julian, CTO and Founder of Netradyne, presents the “Addressing Corner Cases in Embedded Computer Vision Applications” tutorial at the May 2019 Embedded Vision Summit.
Many embedded vision applications require solutions that are robust in the face of very diverse real-world inputs. For example, in automotive applications, vision-based safety systems may encounter unusual configurations of road signs, or unfamiliar temporary barriers around construction sites. In this talk, Julian presents the approach that his company uses to address these “corner cases” in the development of Netradyne’s intelligent driver-safety monitoring system (IDMS).
The essence of the company’ approach is establishing a virtuous cycle which begins with running analytics at the edge and identifying scenarios of interest and corner cases on the embedded edge device. Data from these cases is then uploaded to the cloud, where it is labeled and then utilized for training new deep learning and analytics models. These new models are then deployed to the embedded device to enable improved performance and begin the cycle anew. Juian also looks at how his company uses this virtuous cycle to develop and deploy new features. Additionally, he shows how his company leverages customer expertise to help identify corner cases at scale.