IPDDF: an improved precision dense descriptor based flow estimation

Abstract

Large displacement optical flow algorithms are generally categorised into descriptor-based matching and pixel-based matching. Descriptor-based approaches are robust to geometric variation, however they have inherent localisation precision limitation due to histogram nature. This work presents a novel method called improved precision dense descriptor flow (IPDDF). The authors introduce an additional pixel-based matching cost within an existing dense Daisy descriptor framework to improve the flow estimation precision. Pixel-based features such as pixel colour and gradient are computed on top of the original descriptor in the authors' matching cost formulation. The pixel-based cost only requires a light-weight pre-computation and can be adapted seamlessly into the matching cost formulation. The framework is built based on the Daisy Filter Flow work. In the framework, Daisy descriptor and a filter-based efficient flow inference technique, as well as a randomised fast patch match search algorithm, are adopted. Given the novel matching cost formulation, the framework enables efficiently solving dense correspondence field estimation in a high-dimensional search space, which includes scale and orientation. Experiments on various challenging image pairs demonstrate the proposed algorithm enhances flow estimation accuracy as well as generate a spatially coherent yet edge-aware flow field result efficiently.

Keywords

• optimisation
• filtering theory
• image sequences
• feature extraction
• estimation theory
• image matching
• image segmentation
• object tracking
• pixel-based cost
• light-weight pre-computation
• dense descriptor matching framework
• daisy filter flow work
• filter-based efficient flow inference technique
• novel matching cost formulation
• dense correspondence field estimation
• flow estimation accuracy
• edge-aware flow field
• ipddf
• improved precision dense descriptor based flow estimation
• displacement optical flow algorithms
• descriptor-based approaches
• inherent localisation precision limitation
• precision dense descriptor flow
• additional pixel-based
• existing dense daisy descriptor framework
• flow estimation precision
• pixel-based features
• pixel colour
• original descriptor
• authors