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| Author | M. Danelljan; Fahad Shahbaz Khan; Michael Felsberg; Joost Van de Weijer |
 
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| Title | Adaptive color attributes for real-time visual tracking | Type | Conference Article | |||
| Year | 2014 | Publication | 27th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages  |
1090 - 1097 | |||
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| Abstract | Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object
recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power. This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional variant of color attributes. Both quantitative and attributebased evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24% in median distance precision. Furthermore, we show that our approach outperforms state-of-the-art tracking methods while running at more than 100 frames per second. |
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| Address | Nottingham; UK; September 2014 | |||||
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| Area | Expedition | Conference | CVPR | |||
| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ DKF2014 | Serial | 2509 | |||
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| Author | Daniel Ponsa; Robert Benavente; Felipe Lumbreras; Judit Martinez; Xavier Roca |
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| Title | Quality control of safety belts by machine vision inspection for real-time production | Type | Journal Article | |||
| Year | 2003 | Publication | Optical Engineering (IF: 0.877) | Abbreviated Journal | ||
| Volume | 42 | Issue | 4 | Pages |
1114-1120 | |
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| Publisher | SPIE | Place of Publication | Editor | |||
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| Notes | ADAS;ISE;CIC | Approved | no | |||
| Call Number | ADAS @ adas @ PRL2003 | Serial | 399 | |||
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| Author | Jose Manuel Alvarez; Antonio Lopez; Ramon Baldrich |
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| Title | Illuminant Invariant Model-Based Road Segmentation | Type | Conference Article | |||
| Year | 2008 | Publication | IEEE Intelligent Vehicles Symposium, | Abbreviated Journal | ||
| Volume | Issue | Pages |
1155–1180 | |||
| Keywords | road detection | |||||
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| Address | Eindhoven (The Netherlands) | |||||
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| Notes | ADAS;CIC | Approved | no | |||
| Call Number | ADAS @ adas @ ALB2008 | Serial | 1045 | |||
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| Author | Graham D. Finlayson; Javier Vazquez; Sabine Süsstrunk; Maria Vanrell |
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| Title | Spectral sharpening by spherical sampling | Type | Journal Article | |||
| Year | 2012 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A | |
| Volume | 29 | Issue | 7 | Pages |
1199-1210 | |
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| Abstract | There are many works in color that assume illumination change can be modeled by multiplying sensor responses by individual scaling factors. The early research in this area is sometimes grouped under the heading “von Kries adaptation”: the scaling factors are applied to the cone responses. In more recent studies, both in psychophysics and in computational analysis, it has been proposed that scaling factors should be applied to linear combinations of the cones that have narrower support: they should be applied to the so-called “sharp sensors.” In this paper, we generalize the computational approach to spectral sharpening in three important ways. First, we introduce spherical sampling as a tool that allows us to enumerate in a principled way all linear combinations of the cones. This allows us to, second, find the optimal sharp sensors that minimize a variety of error measures including CIE Delta E (previous work on spectral sharpening minimized RMS) and color ratio stability. Lastly, we extend the spherical sampling paradigm to the multispectral case. Here the objective is to model the interaction of light and surface in terms of color signal spectra. Spherical sampling is shown to improve on the state of the art. | |||||
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| ISSN | 1084-7529 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ FVS2012 | Serial | 2000 | |||
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| Author | Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |
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| Title | An active contour model for speech balloon detection in comics | Type | Conference Article | |||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages |
1240-1244 | |||
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| Abstract | Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent comic book understanding would enable a variety of new applications, including content-based retrieval and content retargeting. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. Few studies have been done in this direction. In this work we detail a novel approach for closed and non-closed speech balloon localization in scanned comic book pages, an essential step towards a fully automatic comic book understanding. The approach is compared with existing methods for closed balloon localization found in the literature and results are presented. | |||||
| Address | washington; USA; August 2013 | |||||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1520-5363 | ISBN | Medium | |||
| Area | Expedition | Conference | ICDAR | |||
| Notes | DAG; CIC; 600.056 | Approved | no | |||
| Call Number | Admin @ si @ RKW2013a | Serial | 2260 | |||
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| Author | Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg |
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| Title | Painting-91: A Large Scale Database for Computational Painting Categorization | Type | Journal Article | |||
| Year | 2014 | Publication | Machine Vision and Applications | Abbreviated Journal | MVAP | |
| Volume | 25 | Issue | 6 | Pages |
1385-1397 | |
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| Abstract | Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms. | |||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | |||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 0932-8092 | ISBN | Medium | |||
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| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ KBW2014 | Serial | 2510 | |||
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| Author | Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell; Dimitris Samaras |
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| Title | The Photometry of Intrinsic Images | Type | Conference Article | |||
| Year | 2014 | Publication | 27th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages |
1494-1501 | |||
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| Abstract | Intrinsic characterization of scenes is often the best way to overcome the illumination variability artifacts that complicate most computer vision problems, from 3D reconstruction to object or material recognition. This paper examines the deficiency of existing intrinsic image models to accurately account for the effects of illuminant color and sensor characteristics in the estimation of intrinsic images and presents a generic framework which incorporates insights from color constancy research to the intrinsic image decomposition problem. The proposed mathematical formulation includes information about the color of the illuminant and the effects of the camera sensors, both of which modify the observed color of the reflectance of the objects in the scene during the acquisition process. By modeling these effects, we get a “truly intrinsic” reflectance image, which we call absolute reflectance, which is invariant to changes of illuminant or camera sensors. This model allows us to represent a wide range of intrinsic image decompositions depending on the specific assumptions on the geometric properties of the scene configuration and the spectral properties of the light source and the acquisition system, thus unifying previous models in a single general framework. We demonstrate that even partial information about sensors improves significantly the estimated reflectance images, thus making our method applicable for a wide range of sensors. We validate our general intrinsic image framework experimentally with both synthetic data and natural images. | |||||
| Address | Columbus; Ohio; USA; June 2014 | |||||
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| Area | Expedition | Conference | CVPR | |||
| Notes | CIC; 600.052; 600.051; 600.074 | Approved | no | |||
| Call Number | Admin @ si @ SPB2014 | Serial | 2506 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Michael Felsberg |
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| Title | Scale Coding Bag-of-Words for Action Recognition | Type | Conference Article | |||
| Year | 2014 | Publication | 22nd International Conference on Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages |
1514-1519 | |||
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| Abstract | Recognizing human actions in still images is a challenging problem in computer vision due to significant amount of scale, illumination and pose variation. Given the bounding box of a person both at training and test time, the task is to classify the action associated with each bounding box in an image.
Most state-of-the-art methods use the bag-of-words paradigm for action recognition. The bag-of-words framework employing a dense multi-scale grid sampling strategy is the de facto standard for feature detection. This results in a scale invariant image representation where all the features at multiple-scales are binned in a single histogram. We argue that such a scale invariant strategy is sub-optimal since it ignores the multi-scale information available with each bounding box of a person. This paper investigates alternative approaches to scale coding for action recognition in still images. We encode multi-scale information explicitly in three different histograms for small, medium and large scale visual-words. Our first approach exploits multi-scale information with respect to the image size. In our second approach, we encode multi-scale information relative to the size of the bounding box of a person instance. In each approach, the multi-scale histograms are then concatenated into a single representation for action classification. We validate our approaches on the Willow dataset which contains seven action categories: interacting with computer, photography, playing music, riding bike, riding horse, running and walking. Our results clearly suggest that the proposed scale coding approaches outperform the conventional scale invariant technique. Moreover, we show that our approach obtains promising results compared to more complex state-of-the-art methods. |
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| Address | Stockholm; August 2014 | |||||
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| Area | Expedition | Conference | ICPR | |||
| Notes | CIC; LAMP; 601.240; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ KWB2014 | Serial | 2450 | |||
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| Author | Xavier Otazu; Oriol Pujol |
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| Title | Wavelet based approach to cluster analysis. Application on low dimensional data sets | Type | Journal Article | |||
| Year | 2006 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL | |
| Volume | 27 | Issue | 14 | Pages |
1590–1605 | |
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| Notes | MILAB; CIC; HuPBA | Approved | no | |||
| Call Number | BCNPCL @ bcnpcl @ OtP2006 | Serial | 658 | |||
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| Author | Noha Elfiky; Fahad Shahbaz Khan; Joost Van de Weijer; Jordi Gonzalez |
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| Title | Discriminative Compact Pyramids for Object and Scene Recognition | Type | Journal Article | |||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR | |
| Volume | 45 | Issue | 4 | Pages |
1627-1636 | |
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| Abstract | Spatial pyramids have been successfully applied to incorporating spatial information into bag-of-words based image representation. However, a major drawback is that it leads to high dimensional image representations. In this paper, we present a novel framework for obtaining compact pyramid representation. First, we investigate the usage of the divisive information theoretic feature clustering (DITC) algorithm in creating a compact pyramid representation. In many cases this method allows us to reduce the size of a high dimensional pyramid representation up to an order of magnitude with little or no loss in accuracy. Furthermore, comparison to clustering based on agglomerative information bottleneck (AIB) shows that our method obtains superior results at significantly lower computational costs. Moreover, we investigate the optimal combination of multiple features in the context of our compact pyramid representation. Finally, experiments show that the method can obtain state-of-the-art results on several challenging data sets. | |||||
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| ISSN | 0031-3203 | ISBN | Medium | |||
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| Notes | ISE; CAT;CIC | Approved | no | |||
| Call Number | Admin @ si @ EKW2012 | Serial | 1807 | |||
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| Author | O. Fors; J. Nuñez; Xavier Otazu; A. Prades; Robert D. Cardinal |
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| Title | Improving the Ability of Image Sensors to Detect Faint Stars and Moving Objects Using Image Deconvolution Techniques | Type | Journal Article | |||
| Year | 2010 | Publication | Sensors | Abbreviated Journal | SENS | |
| Volume | 10 | Issue | 3 | Pages |
1743–1752 | |
| Keywords | image processing; image deconvolution; faint stars; space debris; wavelet transform | |||||
| Abstract | Abstract: In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors. | |||||
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ FNO2010 | Serial | 1285 | |||
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| Author | Marcos V Conde; Florin Vasluianu; Javier Vazquez; Radu Timofte |
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| Title | Perceptual image enhancement for smartphone real-time applications | Type | Conference Article | |||
| Year | 2023 | Publication | Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision | Abbreviated Journal | ||
| Volume | Issue | Pages |
1848-1858 | |||
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| Abstract | Recent advances in camera designs and imaging pipelines allow us to capture high-quality images using smartphones. However, due to the small size and lens limitations of the smartphone cameras, we commonly find artifacts or degradation in the processed images. The most common unpleasant effects are noise artifacts, diffraction artifacts, blur, and HDR overexposure. Deep learning methods for image restoration can successfully remove these artifacts. However, most approaches are not suitable for real-time applications on mobile devices due to their heavy computation and memory requirements. In this paper, we propose LPIENet, a lightweight network for perceptual image enhancement, with the focus on deploying it on smartphones. Our experiments show that, with much fewer parameters and operations, our model can deal with the mentioned artifacts and achieve competitive performance compared with state-of-the-art methods on standard benchmarks. Moreover, to prove the efficiency and reliability of our approach, we deployed the model directly on commercial smartphones and evaluated its performance. Our model can process 2K resolution images under 1 second in mid-level commercial smartphones. | |||||
| Address | Waikoloa; Hawai; USA; January 2023 | |||||
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| Area | Expedition | Conference | WACV | |||
| Notes | MACO; CIC | Approved | no | |||
| Call Number | Admin @ si @ CVV2023 | Serial | 3900 | |||
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| Author | Yawei Li; Yulun Zhang; Radu Timofte; Luc Van Gool; Zhijun Tu; Kunpeng Du; Hailing Wang; Hanting Chen; Wei Li; Xiaofei Wang; Jie Hu; Yunhe Wang; Xiangyu Kong; Jinlong Wu; Dafeng Zhang; Jianxing Zhang; Shuai Liu; Furui Bai; Chaoyu Feng; Hao Wang; Yuqian Zhang; Guangqi Shao; Xiaotao Wang; Lei Lei; Rongjian Xu; Zhilu Zhang; Yunjin Chen; Dongwei Ren; Wangmeng Zuo; Qi Wu; Mingyan Han; Shen Cheng; Haipeng Li; Ting Jiang; Chengzhi Jiang; Xinpeng Li; Jinting Luo; Wenjie Lin; Lei Yu; Haoqiang Fan; Shuaicheng Liu; Aditya Arora; Syed Waqas Zamir; Javier Vazquez; Konstantinos G. Derpanis; Michael S. Brown; Hao Li; Zhihao Zhao; Jinshan Pan; Jiangxin Dong; Jinhui Tang; Bo Yang; Jingxiang Chen; Chenghua Li; Xi Zhang; Zhao Zhang; Jiahuan Ren; Zhicheng Ji; Kang Miao; Suiyi Zhao; Huan Zheng; YanYan Wei; Kangliang Liu; Xiangcheng Du; Sijie Liu; Yingbin Zheng; Xingjiao Wu; Cheng Jin; Rajeev Irny; Sriharsha Koundinya; Vighnesh Kamath; Gaurav Khandelwal; Sunder Ali Khowaja; Jiseok Yoon; Ik Hyun Lee; Shijie Chen; Chengqiang Zhao; Huabin Yang; Zhongjian Zhang; Junjia Huang; Yanru Zhang |
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| Title | NTIRE 2023 challenge on image denoising: Methods and results | Type | Conference Article | |||
| Year | 2023 | Publication | Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops | Abbreviated Journal | ||
| Volume | Issue | Pages |
1904-1920 | |||
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| Abstract | This paper reviews the NTIRE 2023 challenge on image denoising (σ = 50) with a focus on the proposed solutions and results. The aim is to obtain a network design capable to produce high-quality results with the best performance measured by PSNR for image denoising. Independent additive white Gaussian noise (AWGN) is assumed and the noise level is 50. The challenge had 225 registered participants, and 16 teams made valid submissions. They gauge the state-of-the-art for image denoising. | |||||
| Address | Vancouver; Canada; June 2023 | |||||
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| Area | Expedition | Conference | CVPRW | |||
| Notes | MACO; CIC | Approved | no | |||
| Call Number | Admin @ si @ LZT2023 | Serial | 3910 | |||
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| Author | Javier Vazquez; Maria Vanrell; Ramon Baldrich; Francesc Tous |
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| Title | Color Constancy by Category Correlation | Type | Journal Article | |||
| Year | 2012 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP | |
| Volume | 21 | Issue | 4 | Pages |
1997-2007 | |
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| Abstract | Finding color representations which are stable to illuminant changes is still an open problem in computer vision. Until now most approaches have been based on physical constraints or statistical assumptions derived from the scene, while very little attention has been paid to the effects that selected illuminants have
on the final color image representation. The novelty of this work is to propose perceptual constraints that are computed on the corrected images. We define the category hypothesis, which weights the set of feasible illuminants according to their ability to map the corrected image onto specific colors. Here we choose these colors as the universal color categories related to basic linguistic terms which have been psychophysically measured. These color categories encode natural color statistics, and their relevance across different cultures is indicated by the fact that they have received a common color name. From this category hypothesis we propose a fast implementation that allows the sampling of a large set of illuminants. Experiments prove that our method rivals current state-of-art performance without the need for training algorithmic parameters. Additionally, the method can be used as a framework to insert top-down information from other sources, thus opening further research directions in solving for color constancy. |
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| ISSN | 1057-7149 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VVB2012 | Serial | 1999 | |||
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| Author | Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet |
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| Title | Towards multispectral data acquisition with hand-held devices | Type | Conference Article | |||
| Year | 2013 | Publication | 20th IEEE International Conference on Image Processing | Abbreviated Journal | ||
| Volume | Issue | Pages |
2053 - 2057 | |||
| Keywords | Multispectral; mobile devices; color measurements | |||||
| Abstract | 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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| Address | Melbourne; Australia; September 2013 | |||||
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| Area | Expedition | Conference | ICIP | |||
| Notes | CIC; DAG; 600.048 | Approved | no | |||
| Call Number | Admin @ si @ KWK2013b | Serial | 2265 | |||
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| Author | Naila Murray; Luca Marchesotti; Florent Perronnin |
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| 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 | |||
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| 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 | |||||
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| Publisher | IEEE Xplore | Place of Publication | Editor | |||
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| 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 | |||
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| Author | Arjan Gijsenij; Theo Gevers; Joost Van de Weijer |
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| 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. | |||||
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| ISSN | 1057-7149 | ISBN | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | ISE;CIC | Approved | no | |||
| Call Number | Admin @ si @ GGW2011 | Serial | 1717 | |||
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| Author | Robert Benavente; Maria Vanrell; Ramon Baldrich |
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| Title | Parametric Fuzzy Sets for Automatic Color Naming | Type | Journal | |||
| Year | 2008 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | ||
| Volume | 25 | Issue | 10 | Pages |
2582–2593 | |
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| 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 @ BVB2008 | Serial | 1004 | |||
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