# BIT-VO: Visual Odometry at 300 FPS using Binary Features from the Focal Plane

arXiv: https://arxiv.org/abs/2004.11186 · HTML: https://mlsanity.com/paper/2004.11186/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Apr 2020.

## Built on by (most cited first, 4 of 4)

- [Cain: Automatic Code Generation for Simultaneous Convolutional Kernels on Focal-plane Sensor-processors](https://mlsanity.com/paper/2101.08715/) (2021)
- [PixRO: Pixel-Distributed Rotational Odometry with Gaussian Belief Propagation](https://mlsanity.com/paper/2406.09726/) (2024)
- [PixVOD: Pixel-Distributed Direct Visual Odometry and Depth Estimation](https://mlsanity.com/paper/2606.03989/) (2026)
- [Rendering 3D Gaussians on a Graph Processor](https://mlsanity.com/paper/2607.15951/) (2026)

## Abstract (arXiv)

Focal-plane Sensor-processor (FPSP) is a next-generation camera technology which enables every pixel on the sensor chip to perform computation in parallel, on the focal plane where the light intensity is captured. SCAMP-5 is a general-purpose FPSP used in this work and it carries out computations in the analog domain before analog to digital conversion. By extracting features from the image on the focal plane, data which is digitized and transferred is reduced. As a consequence, SCAMP-5 offers a high frame rate while maintaining low energy consumption. Here, we present BIT-VO, which is, to the best of our knowledge, the first 6 Degrees of Freedom visual odometry algorithm which utilises the FPSP. Our entire system operates at 300 FPS in a natural scene, using binary edges and corner features detected by the SCAMP-5.