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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann |
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Title |
When Is A Confidence Measure Good Enough? |
Type |
Conference Article |
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Year |
2013 |
Publication |
9th International Conference on Computer Vision Systems |
Abbreviated Journal |
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Volume |
7963 |
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Pages |
344-353 |
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Keywords |
Optical flow, confidence measure, performance evaluation |
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Abstract |
Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions,
thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality. |
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St Petersburg; Russia; July 2013 |
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Springer Link |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-39401-0 |
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ICVS |
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Notes |
IAM;ADAS; 600.044; 600.057; 600.060; 601.145 |
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Call Number |
IAM @ iam @ MGH2013a |
Serial |
2218 |
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Author |
Katerine Diaz; Francesc J. Ferri; W. Diaz |
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Title |
Fast Approximated Discriminative Common Vectors using rank-one SVD updates |
Type |
Conference Article |
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Year |
2013 |
Publication |
20th International Conference On Neural Information Processing |
Abbreviated Journal |
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Volume |
8228 |
Issue |
III |
Pages |
368-375 |
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Abstract |
An efficient incremental approach to the discriminative common vector (DCV) method for dimensionality reduction and classification is presented. The proposal consists of a rank-one update along with an adaptive restriction on the rank of the null space which leads to an approximate but convenient solution. The algorithm can be implemented very efficiently in terms of matrix operations and space complexity, which enables its use in large-scale dynamic application domains. Deep comparative experimentation using publicly available high dimensional image datasets has been carried out in order to properly assess the proposed algorithm against several recent incremental formulations.
K. Diaz-Chito, F.J. Ferri, W. Diaz |
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Daegu; Korea; November 2013 |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-42050-4 |
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ICONIP |
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ADAS |
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no |
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Call Number |
Admin @ si @ DFD2013 |
Serial |
2439 |
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Author |
Marcelo D. Pistarelli; Angel Sappa; Ricardo Toledo |
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Title |
Multispectral Stereo Image Correspondence |
Type |
Conference Article |
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Year |
2013 |
Publication |
15th International Conference on Computer Analysis of Images and Patterns |
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Volume |
8048 |
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Pages |
217-224 |
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This paper presents a novel multispectral stereo image correspondence approach. It is evaluated using a stereo rig constructed with a visible spectrum camera and a long wave infrared spectrum camera. The novelty of the proposed approach lies on the usage of Hough space as a correspondence search domain. In this way it avoids searching for correspondence in the original multispectral image domains, where information is low correlated, and a common domain is used. The proposed approach is intended to be used in outdoor urban scenarios, where images contain large amount of edges. These edges are used as distinctive characteristics for the matching in the Hough space. Experimental results are provided showing the validity of the proposed approach. |
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York; uk; August 2013 |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-40245-6 |
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CAIP |
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Notes |
ADAS; 600.055 |
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no |
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Call Number |
Admin @ si @ PST2013 |
Serial |
2561 |
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Author |
Gioacchino Vino; Angel Sappa |
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Title |
Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach |
Type |
Conference Article |
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Year |
2013 |
Publication |
10th International Conference on Image Analysis and Recognition |
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Volume |
7950 |
Issue |
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Pages |
354-363 |
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This paper presents an adaptive thresholding approach intended to increase the number of detected corners, while reducing the amount of those ones corresponding to noisy data. The proposed approach works by using the classical Harris corner detector algorithm and overcome the difficulty in finding a general threshold that work well for all the images in a given data set by proposing a novel adaptive thresholding scheme. Initially, two thresholds are used to discern between strong corners and flat regions. Then, a region based criteria is used to discriminate between weak corners and noisy points in the midway interval. Experimental results show that the proposed approach has a better capability to reject false corners and, at the same time, to detect weak ones. Comparisons with the state of the art are provided showing the validity of the proposed approach. |
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Address |
Póvoa de Varzim; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
ISBN |
978-3-642-39093-7 |
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ICIAR |
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Notes |
ADAS; 600.055 |
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no |
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Call Number |
Admin @ si @ ViS2013 |
Serial |
2562 |
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Author |
Jasper Uilings; Koen E.A. van de Sande; Theo Gevers; Arnold Smeulders |
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Title |
Selective Search for Object Recognition |
Type |
Journal Article |
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Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
104 |
Issue |
2 |
Pages |
154-171 |
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Abstract |
This paper addresses the problem of generating possible object locations for use in object recognition. We introduce selective search which combines the strength of both an exhaustive search and segmentation. Like segmentation, we use the image structure to guide our sampling process. Like exhaustive search, we aim to capture all possible object locations. Instead of a single technique to generate possible object locations, we diversify our search and use a variety of complementary image partitionings to deal with as many image conditions as possible. Our selective search results in a small set of data-driven, class-independent, high quality locations, yielding 99 % recall and a Mean Average Best Overlap of 0.879 at 10,097 locations. The reduced number of locations compared to an exhaustive search enables the use of stronger machine learning techniques and stronger appearance models for object recognition. In this paper we show that our selective search enables the use of the powerful Bag-of-Words model for recognition. The selective search software is made publicly available (Software: http://disi.unitn.it/~uijlings/SelectiveSearch.html). |
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0920-5691 |
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Notes |
ALTRES;ISE |
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no |
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Call Number |
Admin @ si @ USG2013 |
Serial |
2362 |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
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Title |
Coloring Action Recognition in Still Images |
Type |
Journal Article |
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Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
105 |
Issue |
3 |
Pages |
205-221 |
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Abstract |
In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification. |
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Springer US |
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ISSN |
0920-5691 |
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Notes |
CIC; ADAS; 600.057; 600.048 |
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no |
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Call Number |
Admin @ si @ KRW2013 |
Serial |
2285 |
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Permanent link to this record |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
A Novel Space Variant Image Representation |
Type |
Journal Article |
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Year |
2013 |
Publication |
Journal of Mathematical Imaging and Vision |
Abbreviated Journal |
JMIV |
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Volume |
47 |
Issue |
1-2 |
Pages |
48-59 |
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Keywords |
Space-variant representation; Log-polar mapping; Onboard vision applications |
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Abstract |
Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. |
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Springer US |
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ISSN |
0924-9907 |
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Notes |
ADAS; 600.055; 605.203; 601.215 |
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no |
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Call Number |
Admin @ si @ OnS2013a |
Serial |
2243 |
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Author |
Sergio Escalera |
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Title |
Multi-Modal Human Behaviour Analysis from Visual Data Sources |
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Journal |
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Year |
2013 |
Publication |
ERCIM News journal |
Abbreviated Journal |
ERCIM |
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Volume |
95 |
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Pages |
21-22 |
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The Human Pose Recovery and Behaviour Analysis group (HuPBA), University of Barcelona, is developing a line of research on multi-modal analysis of humans in visual data. The novel technology is being applied in several scenarios with high social impact, including sign language recognition, assisted technology and supported diagnosis for the elderly and people with mental/physical disabilities, fitness conditioning, and Human Computer Interaction. |
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ISSN |
0926-4981 |
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Notes |
HuPBA;MILAB |
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no |
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Call Number |
Admin @ si @ Esc2013 |
Serial |
2361 |
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Author |
Bogdan Raducanu; Fadi Dornaika |
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Title |
Texture-independent recognition of facial expressions in image snapshots and videos |
Type |
Journal Article |
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Year |
2013 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
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Volume |
24 |
Issue |
4 |
Pages |
811-820 |
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Abstract |
This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines. |
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Springer-Verlag |
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ISSN |
0932-8092 |
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Notes |
OR; 600.046; 605.203;MV |
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no |
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Call Number |
Admin @ si @ RaD2013 |
Serial |
2230 |
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Permanent link to this record |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester |
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Title |
Geometric Steerable Medial Maps |
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Journal Article |
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Year |
2013 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
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Volume |
24 |
Issue |
6 |
Pages |
1255-1266 |
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Keywords |
Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction |
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Abstract |
In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume. |
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Springer Berlin Heidelberg |
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Mubarak Shah |
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0932-8092 |
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Notes |
IAM; 605.203; 600.060; 600.044 |
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no |
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Call Number |
IAM @ iam @ VGB2013 |
Serial |
2192 |
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Permanent link to this record |
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Author |
J.S. Cope; P.Remagnino; S.Mannan; Katerine Diaz; Francesc J. Ferri; P.Wilkin |
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Title |
Reverse Engineering Expert Visual Observations: From Fixations To The Learning Of Spatial Filters With A Neural-Gas Algorithm |
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Journal Article |
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Year |
2013 |
Publication |
Expert Systems with Applications |
Abbreviated Journal |
EXWA |
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40 |
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17 |
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6707-6712 |
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Neural gas; Expert vision; Eye-tracking; Fixations |
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Abstract |
Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give high responses to image regions which a human expert fixated on. These filters can then be used to identify regions in other images which are likely to be useful for a given vision task. The algorithm is evaluated by learning filters for locating specific areas of plant leaves. |
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ISSN |
0957-4174 |
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ADAS |
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no |
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Admin @ si @ CRM2013 |
Serial |
2438 |
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Author |
German Ros; J. Guerrero; Angel Sappa; Antonio Lopez |
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Title |
VSLAM pose initialization via Lie groups and Lie algebras optimization |
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Conference Article |
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Year |
2013 |
Publication |
Proceedings of IEEE International Conference on Robotics and Automation |
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5740 - 5747 |
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SLAM |
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We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm. |
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Karlsruhe; Germany; May 2013 |
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ISSN |
1050-4729 |
ISBN |
978-1-4673-5641-1 |
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ICRA |
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Notes |
ADAS; 600.054; 600.055; 600.057 |
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no |
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Admin @ si @ RGS2013a; ADAS @ adas @ |
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2225 |
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Author |
Mikhail Mozerov |
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Title |
Constrained Optical Flow Estimation as a Matching Problem |
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Journal Article |
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Year |
2013 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
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Volume |
22 |
Issue |
5 |
Pages |
2044-2055 |
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Abstract |
In general, discretization in the motion vector domain yields an intractable number of labels. In this paper we propose an approach that can reduce general optical flow to the constrained matching problem by pre-estimating a 2D disparity labeling map of the desired discrete motion vector function. One of the goals of the proposed paper is estimating coarse distribution of motion vectors and then utilizing this distribution as global constraints for discrete optical flow estimation. This pre-estimation is done with a simple frame-to-frame correlation technique also known as the digital symmetric-phase-only-filter (SPOF). We discover a strong correlation between the output of the SPOF and the motion vector distribution of the related optical flow. The two step matching paradigm for optical flow estimation is applied: pixel accuracy (integer flow), and subpixel accuracy estimation. The matching problem is solved by global optimization. Experiments on the Middlebury optical flow datasets confirm our intuitive assumptions about strong correlation between motion vector distribution of optical flow and maximal peaks of SPOF outputs. The overall performance of the proposed method is promising and achieves state-of-the-art results on the Middlebury benchmark. |
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1057-7149 |
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Admin @ si @ Moz2013 |
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2191 |
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Author |
Mohammad Rouhani; Angel Sappa |
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Title |
The Richer Representation the Better Registration |
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Journal Article |
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2013 |
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IEEE Transactions on Image Processing |
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TIP |
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22 |
Issue |
12 |
Pages |
5036-5049 |
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In this paper, the registration problem is formulated as a point to model distance minimization. Unlike most of the existing works, which are based on minimizing a point-wise correspondence term, this formulation avoids the correspondence search that is time-consuming. In the first stage, the target set is described through an implicit function by employing a linear least squares fitting. This function can be either an implicit polynomial or an implicit B-spline from a coarse to fine representation. In the second stage, we show how the obtained implicit representation is used as an interface to convert point-to-point registration into point-to-implicit problem. Furthermore, we show that this registration distance is smooth and can be minimized through the Levengberg-Marquardt algorithm. All the formulations presented for both stages are compact and easy to implement. In addition, we show that our registration method can be handled using any implicit representation though some are coarse and others provide finer representations; hence, a tradeoff between speed and accuracy can be set by employing the right implicit function. Experimental results and comparisons in 2D and 3D show the robustness and the speed of convergence of the proposed approach. |
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1057-7149 |
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ADAS |
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no |
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Admin @ si @ RoS2013 |
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2665 |
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Author |
Ivo Everts; Jan van Gemert; Theo Gevers |
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Title |
Evaluation of Color STIPs for Human Action Recognition |
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Conference Article |
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Year |
2013 |
Publication |
IEEE Conference on Computer Vision and Pattern Recognition |
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2850-2857 |
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This paper is concerned with recognizing realistic human actions in videos based on spatio-temporal interest points (STIPs). Existing STIP-based action recognition approaches operate on intensity representations of the image data. Because of this, these approaches are sensitive to disturbing photometric phenomena such as highlights and shadows. Moreover, valuable information is neglected by discarding chromaticity from the photometric representation. These issues are addressed by Color STIPs. Color STIPs are multi-channel reformulations of existing intensity-based STIP detectors and descriptors, for which we consider a number of chromatic representations derived from the opponent color space. This enhanced modeling of appearance improves the quality of subsequent STIP detection and description. Color STIPs are shown to substantially outperform their intensity-based counterparts on the challenging UCF~sports, UCF11 and UCF50 action recognition benchmarks. Moreover, the results show that color STIPs are currently the single best low-level feature choice for STIP-based approaches to human action recognition. |
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Portland; oregon; June 2013 |
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1063-6919 |
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CVPR |
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ALTRES;ISE |
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no |
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Call Number |
Admin @ si @ EGG2013 |
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2364 |
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