Low vision assistance with mobile devices

Low vision affects many people, both young and old. Low vision conditions can range from near- and far-sightedness to conditions such as blind spots and tunnel vision. With the growing popularity of mobile devices such as smartphones, there is large opportunity for use of these multipurpose devices to provide low vision assistance. Furthermore, Google\u27s Android operating system provides a robust environment for applications in various fields, including low vision assistance. The objective of this thesis research is to develop a system for low vision assistance that displays important information at the preferred location of the user\u27s visual field. To that end, a first release of a prototype blind spot/tunnel vision assistance system was created and demonstrated on an Android smartphone. Various algorithms for face detection and face tracking were implemented on the Android platform and their performance was assessed with regards to metrics such as throughput and battery usage. Specifically, Viola-Jones, Support Vector Machines, and a color-based method from Pai et al were used for face detection. Template matching, CAMShift, and Lucas-Kanade methods were used for face tracking. It was found that face detection and tracking could be successfully executed within acceptable bounds of time and battery usage, and in some cases performed faster than it would take a comparable cloud-based system for offloading algorithm usage to complete execution

Machine Analysis of Facial Expressions

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GazeDrone: Mobile Eye-Based Interaction in Public Space Without Augmenting the User

Gaze interaction holds a lot of promise for seamless human-computer interaction. At the same time, current wearable mobile eye trackers require user augmentation that negatively impacts natural user behavior while remote trackers require users to position themselves within a confined tracking range. We present GazeDrone, the first system that combines a camera-equipped aerial drone with a computational method to detect sidelong glances for spontaneous (calibration-free) gaze-based interaction with surrounding pervasive systems (e.g., public displays). GazeDrone does not require augmenting each user with on-body sensors and allows interaction from arbitrary positions, even while moving. We demonstrate that drone-supported gaze interaction is feasible and accurate for certain movement types. It is well-perceived by users, in particular while interacting from a fixed position as well as while moving orthogonally or diagonally to a display. We present design implications and discuss opportunities and challenges for drone-supported gaze interaction in public

EyeScout: Active Eye Tracking for Position and Movement Independent Gaze Interaction with Large Public Displays

While gaze holds a lot of promise for hands-free interaction with public displays, remote eye trackers with their confined tracking box restrict users to a single stationary position in front of the display. We present EyeScout, an active eye tracking system that combines an eye tracker mounted on a rail system with a computational method to automatically detect and align the tracker with the user's lateral movement. EyeScout addresses key limitations of current gaze-enabled large public displays by offering two novel gaze-interaction modes for a single user: In "Walk then Interact" the user can walk up to an arbitrary position in front of the display and interact, while in "Walk and Interact" the user can interact even while on the move. We report on a user study that shows that EyeScout is well perceived by users, extends a public display's sweet spot into a sweet line, and reduces gaze interaction kick-off time to 3.5 seconds -- a 62% improvement over state of the art solutions. We discuss sample applications that demonstrate how EyeScout can enable position and movement-independent gaze interaction with large public displays

Unobtrusive and pervasive video-based eye-gaze tracking

Eye-gaze tracking has long been considered a desktop technology that finds its use inside the traditional office setting, where the operating conditions may be controlled. Nonetheless, recent advancements in mobile technology and a growing interest in capturing natural human behaviour have motivated an emerging interest in tracking eye movements within unconstrained real-life conditions, referred to as pervasive eye-gaze tracking. This critical review focuses on emerging passive and unobtrusive video-based eye-gaze tracking methods in recent literature, with the aim to identify different research avenues that are being followed in response to the challenges of pervasive eye-gaze tracking. Different eye-gaze tracking approaches are discussed in order to bring out their strengths and weaknesses, and to identify any limitations, within the context of pervasive eye-gaze tracking, that have yet to be considered by the computer vision community.peer-reviewe

Pedestrian detection in uncontrolled environments using stereo and biometric information

A method for pedestrian detection from challenging real world outdoor scenes is presented in this paper. This technique is able to extract multiple pedestrians, of varying orientations and appearances, from a scene even when faced with large and multiple occlusions. The technique is also robust to changing background lighting conditions and effects, such as shadows. The technique applies an enhanced method from which reliable disparity information can be obtained even from untextured homogeneous areas within a scene. This is used in conjunction with ground plane estimation and biometric information,to obtain reliable pedestrian regions. These regions are robust to erroneous areas of disparity data and also to severe pedestrian occlusion, which often occurs in unconstrained scenarios