Tali Treibitz

@inproceedings { 559, title = {Depth and image restoration from light field in a scattering medium}, booktitle = {The IEEE International Conference on Computer Vision (ICCV)}, year = {2017}, URL = {https://cseweb.ucsd.edu/~ravir/jiand_iccv.pdf}, author = {Tian, Jiandong and Zak Murez and Cui, Tong and Zhang, Zhen and David Kriegman and Ravi Ramamoorthi} }

@article { 555, title = {Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence}, journal = {Nature}, year = {2016}, month = {March}, abstract = {Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22\% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38\%, 33\%, and 41\%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck.}, URL = {http://www.nature.com/articles/srep23166}, author = {Oscar Beijbom and Tali Treibitz and David I. Kline and Gal Eyal and Adi Khen and Benjamin Neal and Yossi Loya and B. Greg Mitchell and David Kriegman} }

@article { 556, title = {Towards automated annotation of benthic survey images: Variability of human experts and operational modes of automation}, journal = {PloS one}, year = {2015}, month = {July}, abstract = {Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50\% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.}, URL = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130312}, author = {Oscar Beijbom and Peter J. Edmunds and Chris Roelfsema and Jennifer Smith and David I. Kline and Benjamin P. Neal and Matthew J Dunlap and Vincent Moriarty and Tung-Yung Fan and Chih-Jui Tan and Stephen Chan and Tali Treibitz and Anthony Gamst and B. Greg Mitchell and David Kriegman} }

@article { 550, title = {Wide Field-of-View Fluorescence Imaging of Coral Reefs}, journal = {Scientific Reports}, year = {2015}, URL = {http://www.nature.com/srep/2015/150109/srep07694/full/srep07694.html}, author = {Tali Treibitz and Benjamin P. Neal and David I. Kline and Oscar Beijbom and Paul L. D. Roberts and B. Greg Mitchell and David Kriegman} }

@inproceedings { 552, title = {Photometric Stereo in a Scattering Medium}, booktitle = {International Conference on Computer Vision (ICCV)}, year = {2015}, abstract = {Photometric stereo is widely used for 3D reconstruction. However, its use in scattering media such as water, biological tissue and fog has been limited until now, because of forward scattered light from both the source and object, as well as light scattered back from the medium (backscatter). Here we make three contributions to address the key modes of light propagation, under the common single scattering assumption for dilute media. First, we show through extensive simulations that single-scattered light from a source can be approximated by a point light source with a single direction. This alleviates the need to handle light source blur explicitly. Next, we model the blur due to scattering of light from the object. We measure the object point-spread function and introduce a simple deconvolution method. Finally, we show how imaging fluorescence emission where available, eliminates the backscatter component and increases the signal-to-noise ratio. Experimental results in a water tank, with different concentrations of scattering media added, show that deconvolution produces higher-quality 3D reconstructions than previous techniques, and that when combined with fluorescence, can produce results similar to that in clear water even for highly turbid media.}, URL = {https://cseweb.ucsd.edu/~ravir/uwps.pdf}, author = {Zak Murez and Tali Treibitz and Ravi Ramamoorthi and David Kriegman} }

@inproceedings { 499, title = {Wide Field-of-View Daytime Fluorescence Imaging of Coral Reefs}, booktitle = {IEEE Oceans}, year = {2013}, URL = {http://www.mtsjournal.org/Papers/PDFs/130502-025.pdf}, author = {Tali Treibitz and Benjamin P. Neal and David I. Kline and Oscar Beijbom and Paul L. D. Roberts and B. Greg Mitchell and David Kriegman} }

@inproceedings { 553, title = {Shape From Fluorescence}, booktitle = {European Conference on Computer Vision (ECCV) }, year = {2012}, author = {Tali Treibitz and Zak Murez and B. Greg Mitchell and David Kriegman} }

@inproceedings { 418, title = {Pose, Illumination and Expression Invariant Pairwise Face-Similarity Measure via Doppelg{\"a}nger List Comparison}, booktitle = {IEEE International Conference on Computer Vision (ICCV)}, year = {2011}, address = {Barcelona}, author = {Florian Schroff and Tali Treibitz and David Kriegman and Serge Belongie} }