Single and Multi-channel Direct Visual Odometry with Binary Descriptors

Visual odometry is a popular area of computer vision that has seen a paradigm shift towards direct methods, where whole image alignment is used to determine camera poses. Current methods not robust to lighting changes in the scene and rely on standard feature-based methods for multi-camera systems. Binary descriptors are an option for alleviating both problems, but current methods do not scale well to larger and more robust descriptors. We present a method for performing direct tracking with binary descriptors of any size by approximating the gradient and descent direction with Hamming weights. We also present alternative methods that approximate the entire descriptor by its Hamming weights. Our results show improved accuracy compared to tracking on intensity alone, and our primary method improves significantly upon similar methods

Distributed Robotic Vision for Calibration, Localisation, and Mapping

This dissertation explores distributed algorithms for calibration, localisation, and mapping in the context of a multi-robot network equipped with cameras and onboard processing, comparing against centralised alternatives where all data is transmitted to a singular external node on which processing occurs. With the rise of large-scale camera networks, and as low-cost on-board processing becomes increasingly feasible in robotics networks, distributed algorithms are becoming important for robustness and scalability. Standard solutions to multi-camera computer vision require the data from all nodes to be processed at a central node which represents a significant single point of failure and incurs infeasible communication costs. Distributed solutions solve these issues by spreading the work over the entire network, operating only on local calculations and direct communication with nearby neighbours. This research considers a framework for a distributed robotic vision platform for calibration, localisation, mapping tasks where three main stages are identified: an initialisation stage where calibration and localisation are performed in a distributed manner, a local tracking stage where visual odometry is performed without inter-robot communication, and a global mapping stage where global alignment and optimisation strategies are applied. In consideration of this framework, this research investigates how algorithms can be developed to produce fundamentally distributed solutions, designed to minimise computational complexity whilst maintaining excellent performance, and designed to operate effectively in the long term. Therefore, three primary objectives are sought aligning with these three stages