Details

Autor(en) / Beteiligte

• Mehrnejad, Marzieh
• Albu, Alexandra Branzan
• Capson, David
• Hoeberechts, Maia

Titel

Detection of stationary animals in deep-sea video

Ist Teil von

• 2013 OCEANS - San Diego, 2013, p.1-5

Ort / Verlag

MTS

Erscheinungsjahr

2013

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• Cabled observatory video data are a rich source of information for marine biologists. However, the large amount of recorded video creates a "big data" problem, which calls for automated detection techniques for sea life. Most of the related research has addressed detection based on animal motion. We propose a novel method for the detection of stationary animals, more precisely for crabs. Our approach integrates shape and color information for the automatic detection of crab and non-crab image patches. With these patches we train a feed-forward neural network, which is further used for classifying image patches into crab and non-crab classes. The experimental evaluation shows very promising results.