Organizing ONSVP Workshop at ICRA 2021
On- and Near-sensor Vision Processing, from Photons to Applications (ONSVP)
Abstract
Almost all real-world AI and robotics applications are power-constrained and depend on real-time understanding of the robot’s environment. Robotic systems that rely on simultaneous localization and mapping (SLAM) and other perception algorithms, would greatly benefit from novel emerging computing paradigms such as computation on or near the focal plane. In this workshop, we explore the emerging unconventional perception methods such as computation directly within the light sensor, performing early-stage recognition before converting signals to digital form, and implementing all or parts of the deep neural networks on the chip. In these methods, only where features of value are identified is data actually transferred to later stages of the vision pipeline. We aim to bring researchers from academia and industry from across multiple disciplines, including i) hardware design, ii) compiler, iii) software/algorithm design, and iv) holistic design to demonstrate the power of novel computational approaches using these unconventional sensors. These novel approaches enable a variety of recognition and tracking applications with exceptionally low latency, high frame rate and low power.
Go to workshop
Invited speakers
- Andrew Davison (Imperial College London)
- Boris Murmann (Stanford University)
- Masatoshi Ishikawa (University of Tokyo)
- Davide Scaramuzza (ETH Zurich / University of Zurich)
- Yu-Hsin Chen (Facebook)
- Christian Braendli (Sony)
- Piotr Dudek (University of Manchester)
- Raluca Scona (Imperial College London)
- Robert Mahony (Australian National University)
- Walterio Mayol-Cuevas (Bristol University)
Topics of interest
They include, but are not limited to:
- Focal-plane Sensor-processor Arrays
- Computational Sensors
- Smart Vision Sensors
- Event Cameras
- Novel Depth Ranging Sensors
- Compiler Methods for Emerging Sensors
- Application in Robotics and AI
- AI on the Focal Plane
- SLAM on Chip/Focal Plane
- Visual/inertial Odometry on Chip/Focal Plane
- Metrics, Benchmarking, and Datasets for the Emerging Sensors
- Performance Analysis of Algorithms and System using Unconventional Sensors
