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A Guidance and Obstacle Evasion Software Framework for Visually Impaired People

A Guidance and Obstacle Evasion Software Framework for Visually Impaired People
Type:Diploma Thesis

, Prof. Dr. Rainer Stiefelhagen

Graduand:Daniel Koester

Information about the environment is desired in several applications, for example autonomous robots and support systems for visually impaired persons. Like with most scenarios where a human being uses a support system, reliability is of utmost importance. This creates a high demand for performance and robustness in real-world settings. Many systems created towards this purpose cannot cope with constraints such as platforms with a large amount of uncontrolled ego-motion and the need for real-time processing of information and are thus not feasible for this specific situation.
The topic of this thesis is a novel framework to create vision based support systems for visually impaired persons. It consists of a modular, easily extendable and highly agile software system. Furthermore, a ground detection system is created to aid in mobile navigation scenarios. The system calculates the accessible section by relying on the assumption that the orientation of a given plane segment can be calculated using a stereo camera reconstruction process.
Many frameworks have been created to simplify the developing process of large and complex systems and to foster collaboration among researchers. Usually, such frameworkswould be created towards a certain purpose, for example a robotic application. In such a scenario, many elements are needed to manage the components of the robotic platform, such as motor controls. This creates dependencies on the availability of specific building blocks and induce great overhead if such components are not needed. Thus, the created framework imposes no restrictions on its use case by moving such functionality into modular components.
In computer vision many features and algorithms to detect ground plane exist. Some of these are quite costly to calculate, for example segmentation based algorithms. Others use a random sample consensus (RANSAC) based approach that shows problems in situations where the existing ground plane only accounts for a small part of the examined input data. To alleviate these problems a simple, yet robust, feature is proposed which consists of a gradient detection in the stereo reconstruction data. The gradient of a region in the disparity map correlates directly with the orientation of a surface in the real world. Since the gradient calculation is not complex, a fast and reliable computation of the accessible section becomes possible.
To evaluate the proposed ground detection system, a dataset was created. This dataset consists of 20 videos recorded with a hand held camera rig and contains a high degree of camera ego-motion to simulate a system worn by a pedestrian. The accessible section detection based on the gradient calculation shows promising results.