This thesis focuses on computer vision and gesture-based human-computer interaction. In examining computer vision, the project covers existing computer vision systems, including OpenNI/NITE and libfreenect. It explores topics such as identifying humans and objects in scenes, recognizing gestures and context-specific movement, and more general scene analysis. The results of the computer vision work are applied to human-computer interaction. The project examines different types of user interfaces and the applicability of gesture-based interaction to those interfaces. One goal is a generic system for controlling user interfaces using a vision-based gesture system. The included software, consisting of three separate projects, covers both high-level HCI and low-level interaction with vision sensor device drivers. HighNI is a set of Java modules for OpenNI and NITE 1.5. It abstracts the existing Java classes to a higher level and provides some skeleton examples for gesture callbacks. OpenNI2-FreenectDriver is a bridge driver that connects OpenNI2's driver interface to libfreenect's API. It allows OpenNI2 to use Kinect hardware on non-Windows platforms where Microsoft's SDK is not available. FreeNUI is a new framework for natural user interaction, based around libfreenect and OpenCV. It is an experimental project that explores interface design and C++11 language features.


Byrnes, Denise


Computer Science


Graphics and Human Computer Interfaces


computer vision, kinect, openni, libfreenect, gesture recognition

Publication Date


Degree Granted

Bachelor of Arts

Document Type

Senior Independent Study Thesis



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