Descriptor-In-Pixel : Point-Feature Tracking For Pixel Processor Arrays
Laurie Bose, Jianing Chen, Piotr Dudek
Abstract
This paper presents a novel approach for joint pointfeature detection and tracking, designed specifically for Pixel Processor Array (PPA) vision sensors. Instead of standard pixels, PPA sensors consist of thousands of "pixelprocessors", enabling massive parallel computation of visual data at the point of light capture. Our approach performs all computation entirely in-pixel, meaning no raw image data need ever leave the sensor for external processing. We introduce a Descriptor-In-Pixel paradigm, in which a feature descriptor is held within the memory of each pixelprocessor. The PPA's architecture enables the response of every processor's descriptor, upon the current image, to be computed in parallel. This produces a"descriptor response map" which, by generating the correct layout of descriptors across the pixel-processors, can be used for both pointfeature detection and tracking. This reduces sensor output to just sparse feature locations and descriptors, read-out via an address-event interface, giving a greater than 1000× reduction in data transfer compared to raw image output. The sparse readout and complete utilization of all pixelprocessors makes our approach very efficient. Our implementation upon the SCAMP-7 PPA prototype runs at over 3000 FPS (Frames Per Second), tracking point-features reliably under violent motion. This is the first work performing point-feature detection and tracking entirely in-pixel. 1
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Install the CLIlune papers fulltext a3989ffc-5feb-4970-b91e-e5502b862ba7Cited by top-tier papers2
- Computer Vision with a Superpixelation CameraSasidharan Mahalingam, Rachel Brown, Atul IngleCVPR 2026
- Focal Plane Visual Feature Generation and Matching on a Pixel Processor ArrayHongyi Zhang, Laurie Bose, Jianing Chen, Piotr Dudek et al.ICCV 2025
Builds on3
- A Camera That CNNs: Towards Embedded Neural Networks on Pixel Processor ArraysLaurie Bose, Piotr Dudek, Jianing Chen, Stephen J. Carey et al.ICCV 2019 · 40 citations
- PixelRNN: In-pixel Recurrent Neural Networks for End-to-end-optimized Perception with Neural SensorsHaley M. So, Laurie Bose, Piotr Dudek, Gordon WetzsteinCVPR 2024 · 9 citations
- Data-Driven Feature Tracking for Event CamerasNico Messikommer, Carter Fang, Mathias Gehrig, Davide ScaramuzzaCVPR 2023
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