PRISM-VO: Scale-Aware Visual Odometry Using Photometric Plenoptic Bundle Adjustment

We introduce PRISM-VO, a novel pure optimization-basedsparse photometric visual odometry framework for focused plenopticcameras. The core of PRISM-VO is a novel photometric plenoptic bun-dle adjustment which jointly optimizes camera poses and inverse depthvalues of points in a sliding window. By combining geometric depth froma single plenoptic image with temporal multi-view constraints, PRISM-VO achieves accurate and drift-resilient motion estimation. Through ex-plicit modeling of the plenoptic projection, PRISM-VO provides reliablemetric-scale reconstructions, overcoming the scale ambiguity of monocu-lar SLAM algorithms. Importantly, our approach relies solely on a singleplenoptic sensor and avoids complex initialization, as depth priors arecomputed directly from plenoptic imaging.Experiments show that PRISM-VO outperforms the current state-of-the-art plenoptic visual odometry method on indoor and outdoor scenes.The proposed approach rivals other optimization- and learning-basedmethods while accurately and reliably recovering a metric scale of thescene.Project page: https://prism-vo.github.io/.