Descriptor-In-Pixel : Point-Feature Tracking For Pixel Processor Arrays
Laurie Bose, Jianing Chen, Piotr Dudek
摘要
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
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- 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 等ICCV 2025
它引用的顶会 Paper3
- A Camera That CNNs: Towards Embedded Neural Networks on Pixel Processor ArraysLaurie Bose, Piotr Dudek, Jianing Chen, Stephen J. Carey 等ICCV 2019 · 被引用 40 次
- PixelRNN: In-pixel Recurrent Neural Networks for End-to-end-optimized Perception with Neural SensorsHaley M. So, Laurie Bose, Piotr Dudek, Gordon WetzsteinCVPR 2024 · 被引用 9 次
- Data-Driven Feature Tracking for Event CamerasNico Messikommer, Carter Fang, Mathias Gehrig, Davide ScaramuzzaCVPR 2023
相关 Paper
- SEAL: A Single-Event Architecture for In-Sensor Visual LocalizationRyan Hou, Thomas Twomey, Vasileios Milionis, Evangelos Dikopoulos 等ISCA 2025 · 被引用 2 次
- DESSCAM: An Event-Driven Architecture with In-Sensor Epitopological Sparse Sampling to Break the Latency-Power Tradeoff in Eye TrackingZhijie Jian, Shangyu Yang, Yuan Hua, Jilin Zhang 等ISCA 2026
- BlissCam: Boosting Eye Tracking Efficiency with Learned In-Sensor Sparse SamplingYu Feng, Tianrui Ma, Yuhao Zhu, Xuan ZhangISCA 2024 · 被引用 14 次
- AllTracker: Efficient Dense Point Tracking at High ResolutionAdam W. Harley, Yang You, Xinglong Sun, Yang Zheng 等ICCV 2025 · 被引用 8 次
- Espresso: Exploiting the Sparsity Property in Event Sensors with Spatiotemporal OrderingLeshan Li, Hongyi Li, Qingyuan Yang, Mingtao Ou 等DAC 2025 · 被引用 1 次
