I see our mates
at Prophesee presenting shortly at the following symposium.
Having some challenges they say and are discussing a stacked event sensor. We know they work with Sony (one of the Chairs for this session) stacked sensor but also acknowledge the emphasis on connectivity to neuromorphic processor architectures....one would trust Akida is one such processor.
Original paper
HERE
2023 Symposium on VLSI Technology and Circuits Advance Program
Circuits Session 22
Advanced Imagers [Suzaku II]
Thursday, June 15, 14:00-15:40
Chairpersons: T. Takahashi, Sony Semiconductor Solutions Corp.
M. Dielacher, Infineon Technologies AG
C22-2 - 14:25
A 320 x 320 1/5" BSI-CMOS Stacked Event Sensor for Low-Power Vision Applications, G. Schon, D. Bourke, P.-A. Doisneau, T. Finateu, A. Gonzalez, N. Hanajima, T. Hitana, L. Janse Van Vuuren, M. Kadry, C. Laurent, F. Le Goff, D. Matolin, A. Mezaour, B. Michel,
T. Naguleswaran, T. Opperman, P. Perrin, E. Reynaud, F. Shahrokhi, H. Tahachouite, C. Tianfan, G. van den Branden, A. Ziram, J.-L. Jaffard and
C. Posch, Prophesee, France
Event-based vision is an emerging paradigm of acquisition and processing of visual information. The highly efficient way of acquiring sparse data and the robustness to uncontrolled lighting conditions make event-based vision attractive for applications in industrial, surveillance, IoT, AR/VR, automotive.
However, the unconventional format of the event data, non-constant data rates, non-standard interfaces pose challenges to usage and integration. A 320x320 6.3μm pixel BSI stacked event sensor was designed with the explicit goal to improve integrability and usability in embedded at-the-edge vision systems.
Emphasis has been put on event data pre-processing and formatting, data interface compatibility and low-latency
connectivity to various processing platforms including low-power uCs and neuromorphic processor architectures.
Furthermore, the sensor has been optimized for ultra-low power operation, featuring a hierarchy of low-power modes and application-specific modes of operation. On-chip power management and an embedded microcontroller core further improve sensor flexibility and useability at-the-edge.