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Author |
J.R. Serra; J.B. Subirana |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Perceptual Grouping on Texture Images Using Non-Cartesian Networks |
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Conference Article |
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1996 |
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IEEE International Conference on Pattern Recognition. Vol B, pp. 462–466 |
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Admin @ si @ SeS1996a |
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217 |
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Author |
X. Binefa; Jordi Vitria |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
A contrast based focusing criterium. |
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1996 |
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IEEE International Conference on Pattern Recognition. Vol. A, pp. 805–809 |
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OR;MV |
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BCNPCL @ bcnpcl @ BiV1996 |
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79 |
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Author |
V. Valev; Petia Radeva |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
A Method of Solving Pattern or image Recognition Problems by Learning Boolean Formulas. |
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Conference Article |
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1992 |
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Proc. of 11th IAPR International Conference on Pattern Recognition |
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II |
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359-362 |
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The Hague, Netherlands |
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IEEE Computer Society Press |
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MILAB |
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BCNPCL @ bcnpcl @ VaR1992b |
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253 |
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Marc Bolaños; R. Mestre; Estefania Talavera; Xavier Giro; Petia Radeva |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Visual Summary of Egocentric Photostreams by Representative Keyframes |
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Conference Article |
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2015 |
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IEEE International Conference on Multimedia and Expo ICMEW2015 |
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1-6 |
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egocentric; lifelogging; summarization; keyframes |
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Building a visual summary from an egocentric photostream captured by a lifelogging wearable camera is of high interest for different applications (e.g. memory reinforcement). In this paper, we propose a new summarization method based on keyframes selection that uses visual features extracted bymeans of a convolutional neural network. Our method applies an unsupervised clustering for dividing the photostreams into events, and finally extracts the most relevant keyframe for each event. We assess the results by applying a blind-taste test on a group of 20 people who assessed the quality of the
summaries. |
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Torino; italy; July 2015 |
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978-1-4799-7079-7 |
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978-1-4799-7079-7 |
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MILAB |
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Admin @ si @ BMT2015 |
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2638 |
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Author |
H. Emrah Tasli; Cevahir Çigla; Theo Gevers; A. Aydin Alatan |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Super pixel extraction via convexity induced boundary adaptation |
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2013 |
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14th IEEE International Conference on Multimedia and Expo |
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1-6 |
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This study presents an efficient super-pixel extraction algorithm with major contributions to the state-of-the-art in terms of accuracy and computational complexity. Segmentation accuracy is improved through convexity constrained geodesic distance utilization; while computational efficiency is achieved by replacing complete region processing with boundary adaptation idea. Starting from the uniformly distributed rectangular equal-sized super-pixels, region boundaries are adapted to intensity edges iteratively by assigning boundary pixels to the most similar neighboring super-pixels. At each iteration, super-pixel regions are updated and hence progressively converging to compact pixel groups. Experimental results with state-of-the-art comparisons, validate the performance of the proposed technique in terms of both accuracy and speed. |
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San Jose; USA; July 2013 |
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1945-7871 |
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ALTRES;ISE |
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Admin @ si @ TÇG2013 |
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2367 |
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Author |
Jaime Moreno; Xavier Otazu |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder |
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Conference Article |
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2011 |
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IEEE International Conference on Multimedia and Expo |
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1-6 |
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In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder. |
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1945-7871 |
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978-1-61284-348-3 |
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CIC |
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Admin @ si @ MoO2011a |
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2176 |
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Author |
D. Jayagopi; Bogdan Raducanu; D. Gatica-Perez |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Characterizing conversational group dynamics using nonverbal behaviour |
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Conference Article |
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Year |
2009 |
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10th IEEE International Conference on Multimedia and Expo |
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370–373 |
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This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members' aggregated acoustical nonverbal behaviour to classify two meeting datasets (one being cooperative-type and the other being competitive-type). We use 4.5 hours of real behavioural multi-party data and show that our methodology can achieve a classification rate of upto 100%. |
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New York, USA |
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1945-7871 |
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978-1-4244-4290-4 |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ JRG2009 |
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1217 |
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Permanent link to this record |
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Author |
Patricia Suarez; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Near InfraRed Imagery Colorization |
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Conference Article |
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Year |
2018 |
Publication |
25th International Conference on Image Processing |
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2237 - 2241 |
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Convolutional Neural Networks (CNN), Generative Adversarial Network (GAN), Infrared Imagery colorization |
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This paper proposes a stacked conditional Generative Adversarial Network-based method for Near InfraRed (NIR) imagery colorization. We propose a variant architecture of Generative Adversarial Network (GAN) that uses multiple
loss functions over a conditional probabilistic generative model. We show that this new architecture/loss-function yields better generalization and representation of the generated colored IR images. The proposed approach is evaluated on a large test dataset and compared to recent state of the art methods using standard metrics. |
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Athens; Greece; October 2018 |
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MSIAU; 600.086; 600.130; 600.122 |
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Admin @ si @ SSV2018b |
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3195 |
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Author |
Marco Buzzelli; Joost Van de Weijer; Raimondo Schettini |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Learning Illuminant Estimation from Object Recognition |
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Conference Article |
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2018 |
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25th International Conference on Image Processing |
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3234 - 3238 |
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Illuminant estimation; computational color constancy; semi-supervised learning; deep learning; convolutional neural networks |
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In this paper we present a deep learning method to estimate the illuminant of an image. Our model is not trained with illuminant annotations, but with the objective of improving performance on an auxiliary task such as object recognition. To the best of our knowledge, this is the first example of a deep
learning architecture for illuminant estimation that is trained without ground truth illuminants. We evaluate our solution on standard datasets for color constancy, and compare it with state of the art methods. Our proposal is shown to outperform most deep learning methods in a cross-dataset evaluation
setup, and to present competitive results in a comparison with parametric solutions. |
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Athens; Greece; October 2018 |
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LAMP; 600.109; 600.120 |
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Admin @ si @ BWS2018 |
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3157 |
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Author |
Victor Vaquero; German Ros; Francesc Moreno-Noguer; Antonio Lopez; Alberto Sanfeliu |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Joint coarse-and-fine reasoning for deep optical flow |
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Conference Article |
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2017 |
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24th International Conference on Image Processing |
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2558-2562 |
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We propose a novel representation for dense pixel-wise estimation tasks using CNNs that boosts accuracy and reduces training time, by explicitly exploiting joint coarse-and-fine reasoning. The coarse reasoning is performed over a discrete classification space to obtain a general rough solution, while the fine details of the solution are obtained over a continuous regression space. In our approach both components are jointly estimated, which proved to be beneficial for improving estimation accuracy. Additionally, we propose a new network architecture, which combines coarse and fine components by treating the fine estimation as a refinement built on top of the coarse solution, and therefore adding details to the general prediction. We apply our approach to the challenging problem of optical flow estimation and empirically validate it against state-of-the-art CNN-based solutions trained from scratch and tested on large optical flow datasets. |
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Beijing; China; September 2017 |
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ADAS; 600.118 |
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Admin @ si @ VRM2017 |
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2898 |
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Author |
Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva |
![download PDF file pdf](img/file_PDF.gif)
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Title |
All the people around me: face clustering in egocentric photo streams |
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Conference Article |
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2017 |
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24th International Conference on Image Processing |
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face discovery; face clustering; deepmatching; bag-of-tracklets; egocentric photo-streams |
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arxiv1703.01790
Given an unconstrained stream of images captured by a wearable photo-camera (2fpm), we propose an unsupervised bottom-up approach for automatic clustering appearing faces into the individual identities present in these data. The problem is challenging since images are acquired under real world conditions; hence the visible appearance of the people in the images undergoes intensive variations. Our proposed pipeline consists of first arranging the photo-stream into events, later, localizing the appearance of multiple people in them, and
finally, grouping various appearances of the same person across different events. Experimental results performed on a dataset acquired by wearing a photo-camera during one month, demonstrate the effectiveness of the proposed approach for the considered purpose. |
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Beijing; China; September 2017 |
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MILAB; no menciona |
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no |
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Admin @ si @ EDR2017 |
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3025 |
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Author |
Andrei Polzounov; Artsiom Ablavatski; Sergio Escalera; Shijian Lu; Jianfei Cai |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
WordFences: Text Localization and Recognition |
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Conference Article |
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2017 |
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24th International Conference on Image Processing |
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Beijing; China; September 2017 |
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HUPBA; no menciona |
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Admin @ si @ PAE2017 |
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3007 |
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Michal Drozdzal; Jordi Vitria; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Intestinal event segmentation for endoluminal video analysis |
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Conference Article |
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2014 |
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21st IEEE International Conference on Image Processing |
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3592 - 3596 |
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Paris; Francia; October 2014 |
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MILAB; OR;MV |
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no |
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Admin @ si @ DVS2014 |
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2565 |
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Author |
Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Towards multispectral data acquisition with hand-held devices |
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Conference Article |
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2013 |
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20th IEEE International Conference on Image Processing |
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2053 - 2057 |
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Multispectral; mobile devices; color measurements |
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We propose a method to acquire multispectral data with handheld devices with front-mounted RGB cameras. We propose to use the display of the device as an illuminant while the camera captures images illuminated by the red, green and
blue primaries of the display. Three illuminants and three response functions of the camera lead to nine response values which are used for reflectance estimation. Results are promising and show that the accuracy of the spectral reconstruction improves in the range from 30-40% over the spectral
reconstruction based on a single illuminant. Furthermore, we propose to compute sensor-illuminant aware linear basis by discarding the part of the reflectances that falls in the sensorilluminant null-space. We show experimentally that optimizing reflectance estimation on these new basis functions decreases
the RMSE significantly over basis functions that are independent to sensor-illuminant. We conclude that, multispectral data acquisition is potentially possible with consumer hand-held devices such as tablets, mobiles, and laptops, opening up applications which are currently considered to be unrealistic. |
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Melbourne; Australia; September 2013 |
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Admin @ si @ KWK2013b |
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2265 |
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Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras |
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Intrinsic Image Evaluation On Synthetic Complex Scenes |
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2013 |
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20th IEEE International Conference on Image Processing |
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285 - 289 |
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Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth
procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes. |
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Melbourne; Australia; September 2013 |
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CIC; 600.048; 600.052; 600.051 |
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Admin @ si @ BSW2013 |
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2264 |
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