Abstract
Environmental monitoring is a critical aspect of marine renewable energy project success. A new system called Unobtrusive Multistatic Serial LiDAR Imager (UMSLI) has been prepared to capture and classify marine life interaction with electrical generation equipment. We present both hardware and software innovations of the UMSLI system. Underwater marine animal imagery has been captured for the first time using red laser diode serial LiDAR, which has advantages over conventional optical cameras in many areas. Moreover, given the scarcity of existing underwater LiDAR data, a shape matching based classification algorithm is proposed which requires few training data. On top of applying shape descriptors, the algorithm also adopts information theoretical learning based affine shape registration, improving point correspondences found by shape descriptors as well as the final similarity measure. Within Florida Atlantic University’s Harbor Branch Oceanographic Institute optical test facility, experimental LiDAR data are collected through the front end of the UMSLI prototype, on which the classification algorithm is validated.
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References
Belongie S, Malik J, Puzicha J (2002) Shape matching and object recognition using shape contexts. PAMI 24(24):509–522
Cao Z, Principe J, Ouyang B (2016) Information point set registration for shape recognition. In: Proc. ICASSP
Cao Z, Principe JC, Ouyang B, Dalgleish F, Vuorenkoski A (2015) Marine animal classification using combined cnn and hand-designed image features. In: OCEANS 2015-MTS/IEEE Washington. IEEE, pp. 1–6
Chen B, Wang J, Zhao H, Zheng N, Principe JC (2015) Convergence of a fixed-point algorithm under maximum correntropy criterion. IEEE Signal Process Lett 22(10):1723–1727
Cormen TH (2009) Introduction to algorithms. MIT Press
Cronkite G, Enzenhofer HJ, Holmes JA, Fisheries D, Oceans Nanaimo BSB (2008) Evaluation of the blueview proviewer 900 imaging sonar as a tool for counting adult sockeye salmon in the Adams river, British Columbia. Tech. rep., DFO. Nanaimo
Dalgleish F (2013) Extended range distributed serial-scan laser imaging in turbid coastal conditions high-resolution laser imagery transmittable from seabed to surface. Sea Technol 54(12):15–+
Dalgleish F, Vuorenkoski A, Nootz G, Ouyang B, Caimi F (2013) Experimental study into the performance impact of the environmental noise on undersea pulsed laser serial imagers. J Underwater Acoust (USN) 61(4)
Dalgleish FR, Vuorenkoski AK, Ouyang B (2013) Extended-range undersea laser imaging: Current research status and a glimpse at future technologies. Mar Technol Soc J 47(5):128–147
Donahue J, Jia Y, Vinyals O, Hoffman J, Zhang N, Tzeng E, Darrell T (2014) Decaf: a deep convolutional activation feature for generic visual recognition. In: ICML, pp 647–655
Donoser M, Riemenschneider H, Bischof H (2009) Efficient partial shape matching of outer contours. In: Asian conference on computer vision. Springer, pp 281–292
Giddings TE, Shirron JJ, Tirat-Gefen A (2005) Eodes-3: an electro-optic imaging and performance prediction model. In: Proceedings of OCEANS 2005 MTS/IEEE. IEEE, pp 1380–1387
Hasanbelliu E, Giraldo LS, Principe JC (2014) Information theoretic shape matching. PAMI 36(12)
Joslin J, Rush B, Stewart A, Polagye B et al (2014) Development of an adaptable monitoring package for marine renewable energy projects part ii: hydrodynamic performance
Ling H, Jacobs DW (2007) Shape classification using the innerdistance. PAMI 29(2):286–299
Liu W, Pokharel PP, Principe JC (2007) Correntropy: properties and applications in non-gaussian signal processing. IEEE Trans Signal Process 55 (11):5286–5298
Ma J, Qiu W, Zhao J, Ma Y, Yuille AL, Tu Z (2015) Robust l2e estimation of transformation for non-rigid registration. IEEE Trans Signal Process 63 (5):1115–1129
Ma J, Zhao J, Yuille AL (2016) Non-rigid point set registration by preserving global and local structures. IEEE Trans Image Process 25(1):53–64
Magowan K, Reitsma J, Murphy D (2012) Use of dual-frequency identification sonar to monitor adult river herring in a small coastal stream. Marine Coastal Fish 4 (1):651–659
Mobley CD (1994) Light and water: radiative transfer in natural waters. Academic Press
Ouyang B (2007) Watermarking based on unified pattern recognition framework. Ph.D. thesis, Southern Methodist University
Ouyang B, Dalgleish F, Caimi F, Vuorenkoski A, Giddings T, Shirron J (2012) Image enhancement for underwater pulsed laser line scan imaging system. In: SPIE Defense, security, and sensing. International Society for Optics and Photonics, pp 83,720r–83,720r
Ouyang B, Dalgleish F, Vuorenkoski A, Britton W, Ramos B, Metzger B (2013) Visualization and image enhancement for multistatic underwater laser line scan system using image-based rendering. IEEE J Ocean Eng 38(3):566–580
Polagye B, Copping A, Suryan R, Kramer S, Brown-Saracino J, Smith C (2014) Instrumentation for monitoring around marine renewable energy converters: workshop final report. PNNL-23110 Pacific Northwest National Laboratory. Seattle
Rother C, Kolmogorov V, Blake A (2004) Grabcut–interactive foreground extraction using iterated graph cuts. ACM Trans Graph 23(3):309–314
Sebastian TB, Klein PN, Kimia BB (2004) Recognition of shapes by editing their shock graphs. IEEE Trans Pattern Anal Mach Intell 26(5):550–571
Wang J, Bai X, You X, Liu W, Latecki LJ (2012) Shape matching and classification using height functions. Pattern Recogn Lett 33(2):134–143
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This work was supported in part by US Department of Energy contract DE-EE0006787 and FAU/HBOI internal fund.
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Cao, Z., Príncipe, J.C., Ouyang, B. et al. Marine animal classification using UMSLI in HBOI optical test facility. Multimed Tools Appl 76, 23117–23138 (2017). https://doi.org/10.1007/s11042-017-4833-4
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DOI: https://doi.org/10.1007/s11042-017-4833-4