dc.contributor.advisor | Chamberland, Jean-Francois | |
dc.creator | Ivanov, Alexander | |
dc.date.accessioned | 2015-06-25T20:08:33Z | |
dc.date.available | 2015-06-25T20:08:33Z | |
dc.date.created | 2012-05 | |
dc.date.issued | 2012-05-03 | |
dc.date.submitted | May 2012 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/154385 | |
dc.description.abstract | This study focuses on the detection and triangulation of sound sources. Specifically, we focus on the detection of sound in order to track a person’s position with a video camera. Acoustic tracking, an alternative to visual tracking, is relatively inexpensive, passive (does not emit energy), and effective in low lighting environments [3]. Our project is broken into two major aspects: accurately discerning input as opposed to background noise and the localization of the sound source. In order to focus on the input signal, we analyze two methods: time averaging and impulse culling. After the sound is analyzed and filtered we focus on the triangulation of the source in 2-D space using direct and estimation techniques requiring three microphones. This process is geared towards finding a compromise between performance and complexity which allows implementation on a standard micro-controller. | en |
dc.format.mimetype | application/pdf | |
dc.subject | Video Tracking | en |
dc.subject | Gauss Markov | en |
dc.subject | Time Difference of Arrival | en |
dc.subject | Acoustic Triangulation | en |
dc.title | Video Tracking Using Acoustic Triangulation | en |
dc.type | Thesis | en |
thesis.degree.department | Electrical and Computer Engineering | en |
thesis.degree.discipline | Electrical Engineering | en |
thesis.degree.grantor | Honors and Undergraduate Research | en |
thesis.degree.name | Bachelor of Science | en |
dc.type.material | text | en |
dc.date.updated | 2015-06-25T20:08:33Z | |