A5087039629- CCD and CMOS Imaging Sensors
- Advanced Memory and Neural Computing
- Infrared Target Detection Methodologies
- Energy Efficient Wireless Sensor Networks
- Transition Metal Oxide Nanomaterials
- Electrical and Bioimpedance Tomography
- Distributed Sensor Networks and Detection Algorithms
Santa Clara University
2024
OmniVision Technologies (United States)
2022
We introduce a hybrid 4096 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 3680 CMOS image sensor (CIS) with an embedded 1032 928 event-based vision (EVS). Within four-by-four cluster of CIS pixels, one color channel is substituted to provide photocurrent for EVS pixel. The readout circuit allocated on second wafer and wrapped behind the pixel cluster. A third used...
Correlated multiple sampling (CMS) is a popular oversampling technique that widely integrated into recent low-noise CMOS image sensors (CISs). In its common implementation equal weights on both reset and signal samples are applied to compute sample. this article, we analyze the effectiveness of four oversampled techniques CIS read noise performance. We compare CMS, optimized correlated (NOCMS), skipper (SMS), (NOSMS). verify our model sensor offering CMS functionality. derive parameters...
Event sensing is a novel modality which solely sensitive to changes of information. This redundancy reduction can be utilized achieve high temporal resolution, reduce power consumption, simplify algorithms etc. The hardware-software co-design event sensors and requires early simulation the sensor system. It has been shown that high-speed video well suited derive such data for contrast based sensors, but simulators published so far neglect phenomena as readout latency or refractory period....
This paper proposes a pixel-wise parameter estimation framework for Event-based Vision Sensor (EVS) characterization. Using an ordinary differential equation (ODE) based pixel latency model and autoregressive Monte-Carlo noise model, we first identify the representative parameters of EVS. The is then formulated as optimization problem to minimize measurement-prediction error both event firing probability. Finally, effectiveness accuracy proposed are verified by comparison synthetic measured...