Vision is the primary means by which we know where we are, what is nearby, and how we are moving. The corresponding computer-vision task is the simultaneous mapping of the surroundings and the localization of the camera. This goes by many names of which this thesis uses Visual Odometry. This name implies the images are sequential and emphasizes the accuracy of the pose and the real time requirements. This field has seen substantial improvements over the past decade and visual odometry is used extensively in robotics for localization, navigation and obstacle detection. 

The main purpose of this thesis is the study and advancement of visual odometry systems, and makes several contributions. The first of which is a high performance stereo visual odometry system, which through geometrically supported tracking achieved top rank on the KITTI odometry benchmark. 

The second is the state-of-the-art perspective three point solver. Such solvers find the pose of a camera given the projections of three known 3d points and are a core part of many visual odometry systems. By reformulating the underlying problem we avoided a problematic quartic polynomial. As a result we achieved substantially higher computational performance and numerical accuracy. 

The third is a system which generalizes stereo visual odometry to the simultaneous estimation of multiple independently moving objects. The main contribution is a real time system which allows the identification of generic moving rigid objects and the prediction of their trajectories in real time, with applications to robotic navigation in in dynamic environments. 

The fourth is an improved spline type continuous pose trajectory estimation framework, which simplifies the integration of general dynamic models. The framework is used to show that visual odometry systems based on continuous pose trajectories are both practical and can operate in real time. 

The visual odometry pipeline is considered from both a theoretical and a practical perspective. The systems described have been tested both on benchmarks and real vehicles. This thesis places the published work into context, highlighting key insights and practical observations.