NEPTUNE Canada possesses a large collection of video data for monitoring marine
life. Such data is important for marine biologists who can observe species in their
natural habitat on a 24/7 basis. It is counterproductive for researchers to manually
search for the events of interest (EOI) in a large database. Our study aims to perform
the automatic detection of the EOI de ned as animal motion. The output of this
approach is in a summary video clip of the original video fi le that contains all salient
events with their associated start and end frames. Our work is based on Laptev [1] spatio-temporal interest points detection method.
Interest points in the 3D spatio-temporal domain (x,y,t) require frame values in local
spatio-temporal volumes to have large variations along all three dimensions. These
local intensity variations are captured in the magnitude of the spatio-temporal derivatives.
We report experimental results on video summarization using a database of videos
from Neptune Canada. The eff ect of several parameters on the performance of the
proposed approach is studied in detail. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/4156 |
| Date | 23 August 2012 |
| Creators | Gebali, Aleya |
| Contributors | Branzan Albu, Alexandra |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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