|
Records |
Links |
|
Author |
Sophie Wuerger; Kaida Xiao; Dimitris Mylonas; Q. Huang; Dimosthenis Karatzas; Galina Paramei |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Blue green color categorization in mandarin english speakers |
Type |
Journal Article |
|
Year |
2012 |
Publication |
Journal of the Optical Society of America A |
Abbreviated Journal |
JOSA A |
|
|
Volume |
29 |
Issue |
2 |
Pages |
A102-A1207 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
Observers are faster to detect a target among a set of distracters if the targets and distracters come from different color categories. This cross-boundary advantage seems to be limited to the right visual field, which is consistent with the dominance of the left hemisphere for language processing [Gilbert et al., Proc. Natl. Acad. Sci. USA 103, 489 (2006)]. Here we study whether a similar visual field advantage is found in the color identification task in speakers of Mandarin, a language that uses a logographic system. Forty late Mandarin-English bilinguals performed a blue-green color categorization task, in a blocked design, in their first language (L1: Mandarin) or second language (L2: English). Eleven color singletons ranging from blue to green were presented for 160 ms, randomly in the left visual field (LVF) or right visual field (RVF). Color boundary and reaction times (RTs) at the color boundary were estimated in L1 and L2, for both visual fields. We found that the color boundary did not differ between the languages; RTs at the color boundary, however, were on average more than 100 ms shorter in the English compared to the Mandarin sessions, but only when the stimuli were presented in the RVF. The finding may be explained by the script nature of the two languages: Mandarin logographic characters are analyzed visuospatially in the right hemisphere, which conceivably facilitates identification of color presented to the LVF. |
|
|
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 |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ WXM2012 |
Serial |
2007 |
|
Permanent link to this record |
|
|
|
|
Author |
Yunchao Gong; Svetlana Lazebnik; Albert Gordo; Florent Perronnin |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Iterative quantization: A procrustean approach to learning binary codes for Large-Scale Image Retrieval |
Type |
Journal Article |
|
Year |
2012 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
|
|
Volume |
35 |
Issue |
12 |
Pages |
2916-2929 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multi-class spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or “classemes” on the ImageNet dataset. |
|
|
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 |
0162-8828 |
ISBN |
978-1-4577-0394-2 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ GLG 2012b |
Serial |
2008 |
|
Permanent link to this record |
|
|
|
|
Author |
Albert Clapes; Miguel Reyes; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis |
Type |
Conference Article |
|
Year |
2012 |
Publication |
7th Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
|
|
|
Volume |
7378 |
Issue |
|
Pages |
1-11 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. |
|
|
Address |
Mallorca |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-31566-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
AMDO |
|
|
Notes |
HUPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ CRE2012 |
Serial |
2010 |
|
Permanent link to this record |
|
|
|
|
Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Monocular Depth-based Background Estimation |
Type |
Conference Article |
|
Year |
2012 |
Publication |
7th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
323-328 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences. |
|
|
Address |
Roma |
|
|
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 |
VISAPP |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e |
Serial |
2012 |
|
Permanent link to this record |
|
|
|
|
Author |
Miguel Oliveira; Angel Sappa; V. Santos |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Color Correction using 3D Gaussian Mixture Models |
Type |
Conference Article |
|
Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
7324 |
Issue |
I |
Pages |
97-106 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
10.1007/978-3-642-31295-3_12 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIAR |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ OSS2012a |
Serial |
2015 |
|
Permanent link to this record |
|
|
|
|
Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Planar-Based Multispectral Stereo |
Type |
Conference Article |
|
Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
|
|
|
Address |
Naples, Italy |
|
|
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 |
QIRT |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ BLA2012 |
Serial |
2016 |
|
Permanent link to this record |
|
|
|
|
Author |
Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
A Novel SIFT-Like-Based Approach for FIR-VS Images Registration |
Type |
Conference Article |
|
Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
|
|
|
Address |
Naples, Italy |
|
|
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 |
QIRT |
|
|
Notes |
ADAS; TV |
Approved |
no |
|
|
Call Number |
Admin @ si @ ABS2012 |
Serial |
2017 |
|
Permanent link to this record |
|
|
|
|
Author |
Monica Piñol; Angel Sappa; Angeles Lopez; Ricardo Toledo |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Feature Selection Based on Reinforcement Learning for Object Recognition |
Type |
Conference Article |
|
Year |
2012 |
Publication |
Adaptive Learning Agents Workshop |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
33-39 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
|
|
|
Address |
Valencia |
|
|
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 |
ALA |
|
|
Notes |
ADAS; RV |
Approved |
no |
|
|
Call Number |
Admin @ si @ PSL2012 |
Serial |
2018 |
|
Permanent link to this record |
|
|
|
|
Author |
Naveen Onkarappa; Angel Sappa |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
An Empirical Study on Optical Flow Accuracy Depending on Vehicle Speed |
Type |
Conference Article |
|
Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1138-1143 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
Driver assistance and safety systems are getting attention nowadays towards automatic navigation and safety. Optical flow as a motion estimation technique has got major roll in making these systems a reality. Towards this, in the current paper, the suitability of polar representation for optical flow estimation in such systems is demonstrated. Furthermore, the influence of individual regularization terms on the accuracy of optical flow on image sequences of different speeds is empirically evaluated. Also a new synthetic dataset of image sequences with different speeds is generated along with the ground-truth optical flow. |
|
|
Address |
Alcalá de Henares |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IV |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ NaS2012 |
Serial |
2020 |
|
Permanent link to this record |
|
|
|
|
Author |
Miguel Oliveira; Angel Sappa; V. Santos |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models |
Type |
Conference Article |
|
Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
299-303 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
|
|
Address |
Alcalá de Henares |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IV |
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ OSS2012b |
Serial |
2021 |
|
Permanent link to this record |
|
|
|
|
Author |
Ivo Everts; Jan van Gemert; Theo Gevers |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Per-patch Descriptor Selection using Surface and Scene Properties |
Type |
Conference Article |
|
Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
|
|
|
Volume |
7577 |
Issue |
VI |
Pages |
172-186 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool. |
|
|
Address |
Florence, Italy |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-33782-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ECCV |
|
|
Notes |
ALTRES;ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ EGG2012 |
Serial |
2023 |
|
Permanent link to this record |
|
|
|
|
Author |
Hamdi Dibeklioglu; Theo Gevers; Albert Ali Salah |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles |
Type |
Conference Article |
|
Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
|
|
|
Volume |
7574 |
Issue |
III |
Pages |
525-538 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, in this paper, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements. The discriminative power of these movements, and the effect of different fusion levels are investigated on multiple databases. Our results improve the state-of-the-art. We also introduce the largest spontaneous/posed enjoyment smile database collected to date, and report new empirical and conceptual findings on smile dynamics. The collected database consists of 1240 samples of 400 subjects. Moreover, it has the unique property of having an age range from 8 to 76 years. Large scale experiments on the new database indicate that eyelid dynamics are highly relevant for smile classification, and there are age-related differences in smile dynamics. |
|
|
Address |
Florence, Italy |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-33711-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ECCV |
|
|
Notes |
ALTRES;ISE |
Approved |
no |
|
|
Call Number |
Admin @ si @ DGS2012 |
Serial |
2024 |
|
Permanent link to this record |
|
|
|
|
Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
AVA: A Large-Scale Database for Aesthetic Visual Analysis |
Type |
Conference Article |
|
Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
2408-2415 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks |
|
|
Address |
Providence, Rhode Islan |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CVPR |
|
|
Notes |
CIC |
Approved |
no |
|
|
Call Number |
Admin @ si @ MMP2012a |
Serial |
2025 |
|
Permanent link to this record |
|
|
|
|
Author |
Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Names and Shades of Color for Intrinsic Image Estimation |
Type |
Conference Article |
|
Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
278-285 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance. |
|
|
Address |
Providence, Rhode Island |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1063-6919 |
ISBN |
978-1-4673-1226-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CVPR |
|
|
Notes |
CIC |
Approved |
no |
|
|
Call Number |
Admin @ si @ SPB2012 |
Serial |
2026 |
|
Permanent link to this record |
|
|
|
|
Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Learning to Rank Images using Semantic and Aesthetic Labels |
Type |
Conference Article |
|
Year |
2012 |
Publication |
23rd British Machine Vision Conference |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
110.1-110.10 |
|
|
Keywords ![sorted by Keywords field, descending order (down)](img/sort_desc.gif) |
|
|
|
Abstract |
Most works on image retrieval from text queries have addressed the problem of retrieving semantically relevant images. However, the ability to assess the aesthetic quality of an image is an increasingly important differentiating factor for search engines. In this work, given a semantic query, we are interested in retrieving images which are semantically relevant and score highly in terms of aesthetics/visual quality. We use large-margin classifiers and rankers to learn statistical models capable of ordering images based on the aesthetic and semantic information. In particular, we compare two families of approaches: while the first one attempts to learn a single ranker which takes into account both semantic and aesthetic information, the second one learns separate semantic and aesthetic models. We carry out a quantitative and qualitative evaluation on a recently-published large-scale dataset and we show that the second family of techniques significantly outperforms the first one. |
|
|
Address |
Guildford, London |
|
|
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 |
1-901725-46-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
BMVC |
|
|
Notes |
CIC |
Approved |
no |
|
|
Call Number |
Admin @ si @ MMP2012b |
Serial |
2027 |
|
Permanent link to this record |