BearCam: Automated Wildlife Monitoring At The
Abstract In this paper we describe the development of the BearCam, a camera system which was deployed in Fall 2005 to monitor the behaviour of grizzly bears at a remote location near the arctic circle. The system aided biologists in collecting the data for their study on bears ’ behavioural response...
| Main Authors: | , , , , , |
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| Format: | Text |
| Language: | English |
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.1196 http://www.cs.sfu.ca/~mori/research/papers/wawerla_bearcam_jmva08.pdf |
| Summary: | Abstract In this paper we describe the development of the BearCam, a camera system which was deployed in Fall 2005 to monitor the behaviour of grizzly bears at a remote location near the arctic circle. The system aided biologists in collecting the data for their study on bears ’ behavioural responses to ecotourists. We developed a camera system for operating in the challenging arctic conditions. We describe a novel “motion shapelet ” algorithm for automatically detecting bears in the video captured by this camera system. This algorithm is an extension of the shapelet features Sabzmeydani and Mori (2007), which are mid-level features capturing pieces of shape. Our extension of this technique incorporates motion information and proves effective at automatically detecting the occurrence of bears. We present quantitative results demonstrating that our algorithm can reliably detect bears in the vast amounts of video footage collected by our system. Keywords object recognition · surveillance · video analysis · boosting · wildlife monitoring |
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