Home | [1–10] << 11 12 13 >> |
Records | Links | |||||
---|---|---|---|---|---|---|
Author | C. Alejandro Parraga; Robert Benavente; Maria Vanrell |
|
||||
Title | Towards a general model of colour categorization which considers context | Type | Journal Article | |||
Year | 2010 | Publication | Perception. ECVP Abstract Supplement | Abbreviated Journal | PER | |
Volume | 39 | Issue | Pages | 86 | ||
Keywords | ||||||
Abstract | In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours. Results from these experiments showed significant dierences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the dierences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that although boundary locations are very similar, boundaries measured in context are significantly dierent(more diuse) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space. |
|||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ PBV2010b | Serial | 1326 | |||
Permanent link to this record | ||||||
Author | C. Alejandro Parraga; Ramon Baldrich; Maria Vanrell |
|
||||
Title | Accurate Mapping of Natural Scenes Radiance to Cone Activation Space: A New Image Dataset | Type | Conference Article | |||
Year | 2010 | Publication | 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science | Abbreviated Journal | ||
Volume | Issue | Pages | 50–57 | |||
Keywords | ||||||
Abstract | The characterization of trichromatic cameras is usually done in terms of a device-independent color space, such as the CIE 1931 XYZ space. This is indeed convenient since it allows the testing of results against colorimetric measures. We have characterized our camera to represent human cone activation by mapping the camera sensor's (RGB) responses to human (LMS) through a polynomial transformation, which can be “customized” according to the types of scenes we want to represent. Here we present a method to test the accuracy of the camera measures and a study on how the choice of training reflectances for the polynomial may alter the results. | |||||
Address | Joensuu, Finland | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | 9781617388897 | Medium | |||
Area | Expedition | Conference | CGIV/MCS | |||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ PBV2010a | Serial | 1322 | |||
Permanent link to this record | ||||||
Author | C. Alejandro Parraga; Olivier Penacchio; Maria Vanrell |
|
||||
Title | Retinal Filtering Matches Natural Image Statistics at Low Luminance Levels | Type | Journal Article | |||
Year | 2011 | Publication | Perception | Abbreviated Journal | PER | |
Volume | 40 | Issue | Pages | 96 | ||
Keywords | ||||||
Abstract | The assumption that the retina’s main objective is to provide a minimum entropy representation to higher visual areas (ie efficient coding principle) allows to predict retinal filtering in space–time and colour (Atick, 1992 Network 3 213–251). This is achieved by considering the power spectra of natural images (which is proportional to 1/f2) and the suppression of retinal and image noise. However, most studies consider images within a limited range of lighting conditions (eg near noon) whereas the visual system’s spatial filtering depends on light intensity and the spatiochromatic properties of natural scenes depend of the time of the day. Here, we explore whether the dependence of visual spatial filtering on luminance match the changes in power spectrum of natural scenes at different times of the day. Using human cone-activation based naturalistic stimuli (from the Barcelona Calibrated Images Database), we show that for a range of luminance levels, the shape of the retinal CSF reflects the slope of the power spectrum at low spatial frequencies. Accordingly, the retina implements the filtering which best decorrelates the input signal at every luminance level. This result is in line with the body of work that places efficient coding as a guiding neural principle. | |||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ PPV2011 | Serial | 1720 | |||
Permanent link to this record | ||||||
Author | C. Alejandro Parraga; Jordi Roca; Maria Vanrell |
|
||||
Title | Do Basic Colors Influence Chromatic Adaptation? | Type | Journal Article | |||
Year | 2011 | Publication | Journal of Vision | Abbreviated Journal | VSS | |
Volume | 11 | Issue | 11 | Pages | 85 | |
Keywords | ||||||
Abstract | Color constancy (the ability to perceive colors relatively stable under different illuminants) is the result of several mechanisms spread across different neural levels and responding to several visual scene cues. It is usually measured by estimating the perceived color of a grey patch under an illuminant change. In this work, we hypothesize whether chromatic adaptation (without a reference white or grey) could be driven by certain colors, specifically those corresponding to the universal color terms proposed by Berlin and Kay (1969). To this end we have developed a new psychophysical paradigm in which subjects adjust the color of a test patch (in CIELab space) to match their memory of the best example of a given color chosen from the universal terms list (grey, red, green, blue, yellow, purple, pink, orange and brown). The test patch is embedded inside a Mondrian image and presented on a calibrated CRT screen inside a dark cabin. All subjects were trained to “recall” their most exemplary colors reliably from memory and asked to always produce the same basic colors when required under several adaptation conditions. These include achromatic and colored Mondrian backgrounds, under a simulated D65 illuminant and several colored illuminants. A set of basic colors were measured for each subject under neutral conditions (achromatic background and D65 illuminant) and used as “reference” for the rest of the experiment. The colors adjusted by the subjects in each adaptation condition were compared to the reference colors under the corresponding illuminant and a “constancy index” was obtained for each of them. Our results show that for some colors the constancy index was better than for grey. The set of best adapted colors in each condition were common to a majority of subjects and were dependent on the chromaticity of the illuminant and the chromatic background considered. | |||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | 1534-7362 | ISBN | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ PRV2011 | Serial | 1759 | |||
Permanent link to this record | ||||||
Author | C. Alejandro Parraga; Jordi Roca; Dimosthenis Karatzas; Sophie Wuerger |
|
||||
Title | Limitations of visual gamma corrections in LCD displays | Type | Journal Article | |||
Year | 2014 | Publication | Displays | Abbreviated Journal | Dis | |
Volume | 35 | Issue | 5 | Pages | 227–239 | |
Keywords | Display calibration; Psychophysics; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration | |||||
Abstract | A method for estimating the non-linear gamma transfer function of liquid–crystal displays (LCDs) without the need of a photometric measurement device was described by Xiao et al. (2011) [1]. It relies on observer’s judgments of visual luminance by presenting eight half-tone patterns with luminances from 1/9 to 8/9 of the maximum value of each colour channel. These half-tone patterns were distributed over the screen both over the vertical and horizontal viewing axes. We conducted a series of photometric and psychophysical measurements (consisting in the simultaneous presentation of half-tone patterns in each trial) to evaluate whether the angular dependency of the light generated by three different LCD technologies would bias the results of these gamma transfer function estimations. Our results show that there are significant differences between the gamma transfer functions measured and produced by observers at different viewing angles. We suggest appropriate modifications to the Xiao et al. paradigm to counterbalance these artefacts which also have the advantage of shortening the amount of time spent in collecting the psychophysical measurements. | |||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | ||||
Notes | CIC; DAG; 600.052; 600.077; 600.074 | Approved | no | |||
Call Number | Admin @ si @ PRK2014 | Serial | 2511 | |||
Permanent link to this record | ||||||
Author | C. Alejandro Parraga; Javier Vazquez; Maria Vanrell |
|
||||
Title | A new cone activation-based natural images dataset | Type | Journal Article | |||
Year | 2009 | Publication | Perception | Abbreviated Journal | PER | |
Volume | 36 | Issue | Pages | 180 | ||
Keywords | ||||||
Abstract | We generated a new dataset of digital natural images where each colour plane corresponds to the human LMS (long-, medium-, short-wavelength) cone activations. The images were chosen to represent five different visual environments (eg forest, seaside, mountain snow, urban, motorways) and were taken under natural illumination at different times of day. At the bottom-left corner of each picture there was a matte grey ball of approximately constant spectral reflectance (across the camera's response spectrum,) and nearly Lambertian reflective properties, which allows to compute (and remove, if necessary) the illuminant's colour and intensity. The camera (Sigma Foveon SD10) was calibrated by measuring its sensor's spectral responses using a set of 31 spectrally narrowband interference filters. This allowed conversion of the final camera-dependent RGB colour space into the Smith and Pokorny (1975) cone activation space by means of a polynomial transformation, optimised for a set of 1269 Munsell chip reflectances. This new method is an improvement over the usual 3 × 3 matrix transformation which is only accurate for spectrally-narrowband colours. The camera-to-LMS transformation can be recalculated to consider other non-human visual systems. The dataset is available to download from our website. | |||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ PVV2009 | Serial | 1193 | |||
Permanent link to this record | ||||||
Author | C. Alejandro Parraga |
|
||||
Title | Color Vision, Computational Methods for | Type | Book Chapter | |||
Year | 2014 | Publication | Encyclopedia of Computational Neuroscience | Abbreviated Journal | ||
Volume | Issue | Pages | 1-11 | |||
Keywords | Color computational vision; Computational neuroscience of color | |||||
Abstract | The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments. | |||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Springer-Verlag Berlin Heidelberg | Place of Publication | Editor | Dieter Jaeger; Ranu Jung | ||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | 978-1-4614-7320-6 | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC; 600.074 | Approved | no | |||
Call Number | Admin @ si @ Par2014 | Serial | 2512 | |||
Permanent link to this record | ||||||
Author | C. Alejandro Parraga |
|
||||
Title | Perceptual Psychophysics | Type | Book Chapter | |||
Year | 2015 | Publication | Biologically-Inspired Computer Vision: Fundamentals and Applications | Abbreviated Journal | ||
Volume | Issue | Pages | ||||
Keywords | ||||||
Abstract | ||||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | G.Cristobal; M.Keil; L.Perrinet | |||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | 978-3-527-41264-8 | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC; 600.074 | Approved | no | |||
Call Number | Admin @ si @ Par2015 | Serial | 2600 | |||
Permanent link to this record | ||||||
Author | Bojana Gajic; Ramon Baldrich |
|
||||
Title | Cross-domain fashion image retrieval | Type | Conference Article | |||
Year | 2018 | Publication | CVPR 2018 Workshop on Women in Computer Vision (WiCV 2018, 4th Edition) | Abbreviated Journal | ||
Volume | Issue | Pages | 19500-19502 | |||
Keywords | ||||||
Abstract | Cross domain image retrieval is a challenging task that implies matching images from one domain to their pairs from another domain. In this paper we focus on fashion image retrieval, which involves matching an image of a fashion item taken by users, to the images of the same item taken in controlled condition, usually by professional photographer. When facing this problem, we have different products
in train and test time, and we use triplet loss to train the network. We stress the importance of proper training of simple architecture, as well as adapting general models to the specific task. |
|||||
Address | Salt Lake City, USA; 22 June 2018 | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | CVPRW | |||
Notes | CIC; 600.087 | Approved | no | |||
Call Number | Admin @ si @ | Serial | 3709 | |||
Permanent link to this record | ||||||
Author | Bojana Gajic; Eduard Vazquez; Ramon Baldrich |
|
||||
Title | Evaluation of Deep Image Descriptors for Texture Retrieval | Type | Conference Article | |||
Year | 2017 | Publication | Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) | Abbreviated Journal | ||
Volume | Issue | Pages | 251-257 | |||
Keywords | Texture Representation; Texture Retrieval; Convolutional Neural Networks; Psychophysical Evaluation | |||||
Abstract | The increasing complexity learnt in the layers of a Convolutional Neural Network has proven to be of great help for the task of classification. The topic has received great attention in recently published literature.
Nonetheless, just a handful of works study low-level representations, commonly associated with lower layers. In this paper, we explore recent findings which conclude, counterintuitively, the last layer of the VGG convolutional network is the best to describe a low-level property such as texture. To shed some light on this issue, we are proposing a psychophysical experiment to evaluate the adequacy of different layers of the VGG network for texture retrieval. Results obtained suggest that, whereas the last convolutional layer is a good choice for a specific task of classification, it might not be the best choice as a texture descriptor, showing a very poor performance on texture retrieval. Intermediate layers show the best performance, showing a good combination of basic filters, as in the primary visual cortex, and also a degree of higher level information to describe more complex textures. |
|||||
Address | Porto, Portugal; 27 February – 1 March 2017 | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | VISIGRAPP | |||
Notes | CIC; 600.087 | Approved | no | |||
Call Number | Admin @ si @ | Serial | 3710 | |||
Permanent link to this record | ||||||
Author | Bojana Gajic; Ariel Amato; Ramon Baldrich; Joost Van de Weijer; Carlo Gatta |
|
||||
Title | Area Under the ROC Curve Maximization for Metric Learning | Type | Conference Article | |||
Year | 2022 | Publication | CVPR 2022 Workshop on Efficien Deep Learning for Computer Vision (ECV 2022, 5th Edition) | Abbreviated Journal | ||
Volume | Issue | Pages | ||||
Keywords | Training; Computer vision; Conferences; Area measurement; Benchmark testing; Pattern recognition | |||||
Abstract | Most popular metric learning losses have no direct relation with the evaluation metrics that are subsequently applied to evaluate their performance. We hypothesize that training a metric learning model by maximizing the area under the ROC curve (which is a typical performance measure of recognition systems) can induce an implicit ranking suitable for retrieval problems. This hypothesis is supported by previous work that proved that a curve dominates in ROC space if and only if it dominates in Precision-Recall space. To test this hypothesis, we design and maximize an approximated, derivable relaxation of the area under the ROC curve. The proposed AUC loss achieves state-of-the-art results on two large scale retrieval benchmark datasets (Stanford Online Products and DeepFashion In-Shop). Moreover, the AUC loss achieves comparable performance to more complex, domain specific, state-of-the-art methods for vehicle re-identification. | |||||
Address | New Orleans, USA; 20 June 2022 | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | CVPRW | |||
Notes | CIC; LAMP; | Approved | no | |||
Call Number | Admin @ si @ GAB2022 | Serial | 3700 | |||
Permanent link to this record | ||||||
Author | Bojana Gajic; Ariel Amato; Ramon Baldrich; Carlo Gatta |
|
||||
Title | Bag of Negatives for Siamese Architectures | Type | Conference Article | |||
Year | 2019 | Publication | 30th British Machine Vision Conference | Abbreviated Journal | ||
Volume | Issue | Pages | ||||
Keywords | ||||||
Abstract | Training a Siamese architecture for re-identification with a large number of identities is a challenging task due to the difficulty of finding relevant negative samples efficiently. In this work we present Bag of Negatives (BoN), a method for accelerated and improved training of Siamese networks that scales well on datasets with a very large number of identities. BoN is an efficient and loss-independent method, able to select a bag of high quality negatives, based on a novel online hashing strategy. | |||||
Address | Cardiff; United Kingdom; September 2019 | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | BMVC | |||
Notes | CIC; 600.140; 600.118 | Approved | no | |||
Call Number | Admin @ si @ GAB2019b | Serial | 3263 | |||
Permanent link to this record | ||||||
Author | Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
|
||||
Title | Computational Color Constancy: Survey and Experiments | Type | Journal Article | |||
Year | 2011 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP | |
Volume | 20 | Issue | 9 | Pages | 2475-2489 | |
Keywords | computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting | |||||
Abstract | Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets. | |||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | 1057-7149 | ISBN | Medium | |||
Area | Expedition | Conference | ||||
Notes | ISE;CIC | Approved | no | |||
Call Number | Admin @ si @ GGW2011 | Serial | 1717 | |||
Permanent link to this record | ||||||
Author | Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
|
||||
Title | Improving Color Constancy by Photometric Edge Weighting | Type | Journal Article | |||
Year | 2012 | Publication | IEEE Transaction on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI | |
Volume | 34 | Issue | 5 | Pages | 918-929 | |
Keywords | ||||||
Abstract | : Edge-based color constancy methods make use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as material, shadow and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant estimation. Therefore, in this paper, an extensive analysis is provided of different edge types on the performance of edge-based color constancy methods. First, an edge-based taxonomy is presented classifying edge types based on their photometric properties (e.g. material, shadow-geometry and highlights). Then, a performance evaluation of edge-based color constancy is provided using these different edge types. From this performance evaluation it is derived that specular and shadow edge types are more valuable than material edges for the estimation of the illuminant. To this end, the (iterative) weighted Grey-Edge algorithm is proposed in which these edge types are more emphasized for the estimation of the illuminant. Images that are recorded under controlled circumstances demonstrate that the proposed iterative weighted Grey-Edge algorithm based on highlights reduces the median angular error with approximately $25\%$. In an uncontrolled environment, improvements in angular error up to $11\%$ are obtained with respect to regular edge-based color constancy. | |||||
Address | Los Alamitos; CA; USA; | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | 0162-8828 | ISBN | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC;ISE | Approved | no | |||
Call Number | Admin @ si @ GGW2012 | Serial | 1850 | |||
Permanent link to this record | ||||||
Author | Antonio Lopez; J. Hilgenstock; A. Busse; Ramon Baldrich; Felipe Lumbreras; Joan Serrat |
|
||||
Title | Nightime Vehicle Detecion for Intelligent Headlight Control | Type | Conference Article | |||
Year | 2008 | Publication | Advanced Concepts for Intelligent Vision Systems, 10th International Conference, Proceedings, | Abbreviated Journal | ||
Volume | 5259 | Issue | Pages | 113–124 | ||
Keywords | Intelligent Headlights; vehicle detection | |||||
Abstract | ||||||
Address | Juan-les-Pins, France | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | LNCS | |||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | ACIVS | |||
Notes | ADAS;CIC | Approved | no | |||
Call Number | ADAS @ adas @ LHB2008a | Serial | 1098 | |||
Permanent link to this record | ||||||
Author | Antonio Lopez; J. Hilgenstock; A. Busse; Ramon Baldrich; Felipe Lumbreras; Joan Serrat |
|
||||
Title | Temporal Coherence Analysis for Intelligent Headlight Control | Type | Miscellaneous | |||
Year | 2008 | Publication | 2nd Workshop on Perception, Planning and Navigation for Intelligent Vehicles | Abbreviated Journal | ||
Volume | Issue | Pages | 59–64 | |||
Keywords | Intelligent Headlights | |||||
Abstract | ||||||
Address | ||||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | IROS | |||
Notes | ADAS;CIC | Approved | no | |||
Call Number | ADAS @ adas @ LHB2008b | Serial | 1112 | |||
Permanent link to this record | ||||||
Author | Anna Salvatella; Maria Vanrell; Ramon Baldrich |
|
||||
Title | Subtexture Components for Texture Description | Type | Conference Article | |||
Year | 2003 | Publication | 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 | Abbreviated Journal | ||
Volume | 2652 | Issue | Pages | 884-892 | ||
Keywords | ||||||
Abstract | ||||||
Address | Springer-Verlag | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | LNCS | |||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | Medium | ||||
Area | Expedition | Conference | IbPRIA | |||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ SVR2003 | Serial | 421 | |||
Permanent link to this record | ||||||
Author | Anna Salvatella; Maria Vanrell; Juan J. Villanueva |
|
||||
Title | Texture Description based on Subtexture Components, 3rd International Workshop on Texture Syntesis and Analysis | Type | Conference Article | |||
Year | 2003 | Publication | 3rd International Workshop on Texture Synthesis and Analysis, | Abbreviated Journal | ||
Volume | Issue | Pages | 77–82 | |||
Keywords | ||||||
Abstract | ||||||
Address | Nice | |||||
Corporate Author | Thesis | |||||
Publisher | Place of Publication | Editor | ||||
Language | Summary Language | Original Title | ||||
Series Editor | Series Title | Abbreviated Series Title | ||||
Series Volume | Series Issue | Edition | ||||
ISSN | ISBN | 1-904410-11-1 | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ SVV2003 | Serial | 422 | |||
Permanent link to this record |