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Author | Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco | ||||
Title | An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction | Type | Conference Article | ||
Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | |
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Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM).
This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here. |
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Area | Expedition | Conference | AV A | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ OPD2012a | Serial | 2132 | ||
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Author | Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre | ||||
Title | Multi-oriented touching text character segmentation in graphical documents using dynamic programming | Type | Journal Article | ||
Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 45 | Issue | 5 | Pages | 1972-1983 |
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Abstract | 2,292 JCR
The touching character segmentation problem becomes complex when touching strings are multi-oriented. Moreover in graphical documents sometimes characters in a single-touching string have different orientations. Segmentation of such complex touching is more challenging. In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region in the background portion. Based on the convex hull information, at first, we use this background information to find some initial points for segmentation of a touching string into possible primitives (a primitive consists of a single character or part of a character). Next, the primitives are merged to get optimum segmentation. A dynamic programming algorithm is applied for this purpose using the total likelihood of characters as the objective function. A SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Experiments were performed in different databases of real and synthetic touching characters and the results show that the method is efficient in segmenting touching characters of arbitrary orientations and sizes. |
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ISSN | 0031-3203 | ISBN | Medium | ||
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ RPL2012a | Serial | 2133 | ||
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Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
Title | Text line extraction in graphical documents using background and foreground | Type | Journal Article | ||
Year | 2012 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
Volume | 15 | Issue | 3 | Pages | 227-241 |
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Abstract | 0,405 JCR
In graphical documents (e.g., maps, engineering drawings), artistic documents etc., the text lines are annotated in multiple orientations or curvilinear way to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted. In this paper, we propose a novel method to segment such text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. In the proposed scheme, at first, individual components are detected and grouped into character clusters in a hierarchical way using size and positional information. Next, the clusters are extended in two extreme sides to determine potential candidate regions. Finally, with the help of these candidate regions, individual lines are extracted. The experimental results are presented on different datasets of graphical documents, camera-based warped documents, noisy images containing seals, etc. The results demonstrate that our approach is robust and invariant to size and orientation of the text lines present in the document. |
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ISSN | 1433-2833 | ISBN | Medium | ||
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ RPL2012b | Serial | 2134 | ||
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Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
Title | Text/graphic separation using a sparse representation with multi-learned dictionaries | Type | Conference Article | ||
Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
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Keywords | Graphics Recognition; Layout Analysis; Document Understandin | ||||
Abstract | In this paper, we propose a new approach to extract text regions from graphical documents. In our method, we first empirically construct two sequences of learned dictionaries for the text and graphical parts respectively. Then, we compute the sparse representations of all different sizes and non-overlapped document patches in these learned dictionaries. Based on these representations, each patch can be classified into the text or graphic category by comparing its reconstruction errors. Same-sized patches in one category are then merged together to define the corresponding text or graphic layers which are combined to createfinal text/graphic layer. Finally, in a post-processing step, text regions are further filtered out by using some learned thresholds. | ||||
Address | Tsukuba | ||||
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Area | Expedition | Conference | ICPR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DTR2012a | Serial | 2135 | ||
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Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
Title | Noise suppression over bi-level graphical documents using a sparse representation | Type | Conference Article | ||
Year | 2012 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
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Address | Bordeaux | ||||
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Area | Expedition | Conference | CIFED | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DTR2012b | Serial | 2136 | ||
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Author | Adriana Romero; Simeon Petkov; Carlo Gatta; M.Sabate; Petia Radeva | ||||
Title | Efficient automatic segmentation of vessels | Type | Conference Article | ||
Year | 2012 | Publication | 16th Conference on Medical Image Understanding and Analysis | Abbreviated Journal | |
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Address | Swansea, United Kingdom | ||||
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Area | Expedition | Conference | MIUA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ | Serial | 2137 | ||
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Author | Pedro Martins; Carlo Gatta; Paulo Carvalho | ||||
Title | Feature-driven Maximally Stable Extremal Regions | Type | Conference Article | ||
Year | 2012 | Publication | 7th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | Issue | Pages | 490-497 | ||
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Area | Expedition | Conference | VISAPP | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ MGC2012 | Serial | 2139 | ||
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Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
Title | Context Aware Keypoint Extraction for Robust Image Representation | Type | Conference Article | ||
Year | 2012 | Publication | 23rd British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | 100.1 - 100.12 | ||
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Area | Expedition | Conference | BMVC | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ MCG2012a | Serial | 2140 | ||
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Author | Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin-Yuste; Manel Sabate; Petia Radeva | ||||
Title | Accurate coronary centerline extraction, caliber estimation and catheter detection in angiographies | Type | Journal Article | ||
Year | 2012 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
Volume | 16 | Issue | 6 | Pages | 1332-1340 |
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Abstract | Segmentation of coronary arteries in X-Ray angiography is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities which allows physicians rapid access to different medical imaging information from Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). In this paper, we propose an accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection. Vesselness, geodesic paths, and a new multi-scale edgeness map are combined to customize the Graph-cuts approach to the segmentation of tubular structures, by means of a global optimization of the Graph-cuts energy function. Moreover, a novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection. We evaluate the method performance on three datasets coming from different imaging systems. The method performs as good as the expert observer w.r.t. centerline detection and caliber estimation. Moreover, the method discriminates between arteries and catheter with an accuracy of 96.5%, sensitivity of 72%, and precision of 97.4%. | ||||
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ISSN | 1089-7771 | ISBN | Medium | ||
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ HGE2012 | Serial | 2141 | ||
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Author | Josep M. Gonfaus; Theo Gevers; Arjan Gijsenij; Xavier Roca; Jordi Gonzalez | ||||
Title | Edge Classification using Photo-Geo metric features | Type | Conference Article | ||
Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1497 - 1500 | ||
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Abstract | Edges are caused by several imaging cues such as shadow, material and illumination transitions. Classification methods have been proposed which are solely based on photometric information, ignoring geometry to classify the physical nature of edges in images. In this paper, the aim is to present a novel strategy to handle both photometric and geometric information for edge classification. Photometric information is obtained through the use of quasi-invariants while geometric information is derived from the orientation and contrast of edges. Different combination frameworks are compared with a new principled approach that captures both information into the same descriptor. From large scale experiments on different datasets, it is shown that, in addition to photometric information, the geometry of edges is an important visual cue to distinguish between different edge types. It is concluded that by combining both cues the performance improves by more than 7% for shadows and highlights. | ||||
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ISSN | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
Area | Expedition | Conference | ICPR | ||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ GGG2012b | Serial | 2142 | ||
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Author | Laura Igual; Joan Carles Soliva; Sergio Escalera; Roger Gimeno; Oscar Vilarroya; Petia Radeva | ||||
Title | Automatic Brain Caudate Nuclei Segmentation and Classification in Diagnostic of Attention-Deficit/Hyperactivity Disorder | Type | Journal Article | ||
Year | 2012 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
Volume | 36 | Issue | 8 | Pages | 591-600 |
Keywords | Automatic caudate segmentation; Attention-Deficit/Hyperactivity Disorder; Diagnostic test; Machine learning; Decision stumps; Dissociated dipoles | ||||
Abstract | We present a fully automatic diagnostic imaging test for Attention-Deficit/Hyperactivity Disorder diagnosis assistance based on previously found evidences of caudate nucleus volumetric abnormalities. The proposed method consists of different steps: a new automatic method for external and internal segmentation of caudate based on Machine Learning methodologies; the definition of a set of new volume relation features, 3D Dissociated Dipoles, used for caudate representation and classification. We separately validate the contributions using real data from a pediatric population and show precise internal caudate segmentation and discrimination power of the diagnostic test, showing significant performance improvements in comparison to other state-of-the-art methods. | ||||
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Notes | OR; HuPBA; MILAB | Approved | no | ||
Call Number | Admin @ si @ ISE2012 | Serial | 2143 | ||
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Author | Antonio Hernandez; Miguel Reyes; Victor Ponce; Sergio Escalera | ||||
Title | GrabCut-Based Human Segmentation in Video Sequences | Type | Journal Article | ||
Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 12 | Issue | 11 | Pages | 15376-15393 |
Keywords | segmentation; human pose recovery; GrabCut; GraphCut; Active Appearance Models; Conditional Random Field | ||||
Abstract | In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology. | ||||
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Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ HRP2012 | Serial | 2147 | ||
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Author | Petia Radeva; Michal Drozdzal; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
Title | Active labeling: Application to wireless endoscopy analysis | Type | Conference Article | ||
Year | 2012 | Publication | High Performance Computing and Simulation, International Conference on | Abbreviated Journal | |
Volume | Issue | Pages | 174-181 | ||
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Abstract | Today, robust learners trained in a real supervised machine learning application should count with a rich collection of positive and negative examples. Although in many applications, it is not difficult to obtain huge amount of data, labeling those data can be a very expensive process, especially when dealing with data of high variability and complexity. A good example of such cases are data from medical imaging applications where annotating anomalies like tumors, polyps, atherosclerotic plaque or informative frames in wireless endoscopy need highly trained experts. Building a representative set of training data from medical videos (e.g. Wireless Capsule Endoscopy) means that thousands of frames to be labeled by an expert. It is quite normal that data in new videos come different and thus are not represented by the training set. In this paper, we review the main approaches on active learning and illustrate how active learning can help to reduce expert effort in constructing the training sets. We show that applying active learning criteria, the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of Wireless Capsule Endoscopy video containing more than 30000 frames each one with less than 100 expert ”clicks”. | ||||
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ISSN | ISBN | 978-1-4673-2359-8 | Medium | ||
Area | Expedition | Conference | HPCS | ||
Notes | MILAB; OR;MV | Approved | no | ||
Call Number | Admin @ si @ RDS2012 | Serial | 2152 | ||
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Author | Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo | ||||
Title | Multispectral Image Feature Points | Type | Journal Article | ||
Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 12 | Issue | 9 | Pages | 12661-12672 |
Keywords | multispectral image descriptor; color and infrared images; feature point descriptor | ||||
Abstract | Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. | ||||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ ABL2012 | Serial | 2154 | ||
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Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
Title | Multimodal Stereo Vision System: 3D Data Extraction and Algorithm Evaluation | Type | Journal Article | ||
Year | 2012 | Publication | IEEE Journal of Selected Topics in Signal Processing | Abbreviated Journal | J-STSP |
Volume | 6 | Issue | 5 | Pages | 437-446 |
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Abstract | This paper proposes an imaging system for computing sparse depth maps from multispectral images. A special stereo head consisting of an infrared and a color camera defines the proposed multimodal acquisition system. The cameras are rigidly attached so that their image planes are parallel. Details about the calibration and image rectification procedure are provided. Sparse disparity maps are obtained by the combined use of mutual information enriched with gradient information. The proposed approach is evaluated using a Receiver Operating Characteristics curve. Furthermore, a multispectral dataset, color and infrared images, together with their corresponding ground truth disparity maps, is generated and used as a test bed. Experimental results in real outdoor scenarios are provided showing its viability and that the proposed approach is not restricted to a specific domain. | ||||
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ISSN | 1932-4553 | ISBN | Medium | ||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ BLS2012b | Serial | 2155 | ||
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