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Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate |
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Title |
Local Analysis of Confidence Measures for Optical Flow Quality Evaluation |
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Conference Article |
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Year |
2014 |
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9th International Conference on Computer Vision Theory and Applications |
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3 |
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450-457 |
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Optical Flow; Confidence Measure; Performance Evaluation. |
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Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance. |
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Lisboa; January 2014 |
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VISAPP |
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IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 |
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Admin @ si @ MGM2014 |
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2432 |
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Sergio Escalera; Xavier Baro; Jordi Gonzalez; Miguel Angel Bautista; Meysam Madadi; Miguel Reyes; Victor Ponce; Hugo Jair Escalante; Jaime Shotton; Isabelle Guyon |
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Title |
ChaLearn Looking at People Challenge 2014: Dataset and Results |
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Conference Article |
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2014 |
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ECCV Workshop on ChaLearn Looking at People |
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8925 |
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459-473 |
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Human Pose Recovery; Behavior Analysis; Action and in- teractions; Multi-modal gestures; recognition |
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This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. The competition was split into three independent tracks: human pose recovery from RGB data, action and interaction recognition from RGB data sequences, and multi-modal gesture recognition from RGB-Depth sequences. For all the tracks, the goal was to perform user-independent recognition in sequences of continuous images using the overlapping Jaccard index as the evaluation measure. In this edition of the ChaLearn challenge, two large novel data sets were made publicly available and the Microsoft Codalab platform were used to manage the competition. Outstanding results were achieved in the three challenge tracks, with accuracy results of 0.20, 0.50, and 0.85 for pose recovery, action/interaction recognition, and multi-modal gesture recognition, respectively. |
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ECCVW |
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HuPBA; ISE; 600.063;MV |
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Admin @ si @ EBG2014 |
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2529 |
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David Fernandez; Pau Riba; Alicia Fornes; Josep Llados |
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On the Influence of Key Point Encoding for Handwritten Word Spotting |
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Conference Article |
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2014 |
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14th International Conference on Frontiers in Handwriting Recognition |
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476 - 481 |
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Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis |
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In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries. |
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Creete Island; Grecia; September 2014 |
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2167-6445 |
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978-1-4799-4335-7 |
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ICFHR |
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DAG; 600.056; 600.061; 602.006; 600.077 |
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no |
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Admin @ si @ FRF2014 |
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2460 |
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Bogdan Raducanu; Fadi Dornaika |
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Embedding new observations via sparse-coding for non-linear manifold learning |
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Journal Article |
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Year |
2014 |
Publication |
Pattern Recognition |
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PR |
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47 |
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1 |
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480-492 |
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Non-linear dimensionality reduction techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data-the out-of-sample problem. For the first aspect, the proposed solutions, in general, were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only achieved for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that the sparse representation theory not only serves for automatic graph construction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the K-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on six public face datasets. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes. |
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LAMP; |
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no |
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Admin @ si @ RaD2013b |
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2316 |
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Author |
B. Zhou; Agata Lapedriza; J. Xiao; A. Torralba; A. Oliva |
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Title |
Learning Deep Features for Scene Recognition using Places Database |
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Conference Article |
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Year |
2014 |
Publication |
28th Annual Conference on Neural Information Processing Systems |
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487-495 |
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Montreal; Canada; December 2014 |
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NIPS |
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OR;MV |
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no |
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Admin @ si @ ZLX2014 |
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2621 |
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Author |
Josep Llados; Marçal Rusiñol |
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Title |
Graphics Recognition Techniques |
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Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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D |
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489-521 |
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Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation |
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Abstract |
This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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no |
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Admin @ si @ LlR2014 |
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2380 |
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Author |
Carlo Gatta; Adriana Romero; Joost Van de Weijer |
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Title |
Unrolling loopy top-down semantic feedback in convolutional deep networks |
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Conference Article |
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2014 |
Publication |
Workshop on Deep Vision: Deep Learning for Computer Vision |
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498-505 |
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In this paper, we propose a novel way to perform top-down semantic feedback in convolutional deep networks for efficient and accurate image parsing. We also show how to add global appearance/semantic features, which have shown to improve image parsing performance in state-of-the-art methods, and was not present in previous convolutional approaches. The proposed method is characterised by an efficient training and a sufficiently fast testing. We use the well known SIFTflow dataset to numerically show the advantages provided by our contributions, and to compare with state-of-the-art image parsing convolutional based approaches. |
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Columbus; Ohio; June 2014 |
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CVPRW |
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LAMP; MILAB; 601.160; 600.079 |
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no |
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Admin @ si @ GRW2014 |
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2490 |
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Author |
Palaiahnakote Shivakumara; Anjan Dutta; Chew Lim Tan; Umapada Pal |
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Title |
Multi-oriented scene text detection in video based on wavelet and angle projection boundary growing |
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Journal Article |
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2014 |
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Multimedia Tools and Applications |
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MTAP |
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72 |
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1 |
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515-539 |
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In this paper, we address two complex issues: 1) Text frame classification and 2) Multi-oriented text detection in video text frame. We first divide a video frame into 16 blocks and propose a combination of wavelet and median-moments with k-means clustering at the block level to identify probable text blocks. For each probable text block, the method applies the same combination of feature with k-means clustering over a sliding window running through the blocks to identify potential text candidates. We introduce a new idea of symmetry on text candidates in each block based on the observation that pixel distribution in text exhibits a symmetric pattern. The method integrates all blocks containing text candidates in the frame and then all text candidates are mapped on to a Sobel edge map of the original frame to obtain text representatives. To tackle the multi-orientation problem, we present a new method called Angle Projection Boundary Growing (APBG) which is an iterative algorithm and works based on a nearest neighbor concept. APBG is then applied on the text representatives to fix the bounding box for multi-oriented text lines in the video frame. Directional information is used to eliminate false positives. Experimental results on a variety of datasets such as non-horizontal, horizontal, publicly available data (Hua’s data) and ICDAR-03 competition data (camera images) show that the proposed method outperforms existing methods proposed for video and the state of the art methods for scene text as well. |
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Springer US |
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1380-7501 |
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DAG; 600.077 |
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no |
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Admin @ si @ SDT2014 |
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2357 |
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Author |
Salvatore Tabbone; Oriol Ramos Terrades |
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An Overview of Symbol Recognition |
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Book Chapter |
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2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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D |
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523-551 |
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Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting |
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According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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no |
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Admin @ si @ TaT2014 |
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2489 |
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Marçal Rusiñol; Lluis Pere de las Heras; Oriol Ramos Terrades |
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Title |
Flowchart Recognition for Non-Textual Information Retrieval in Patent Search |
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Journal Article |
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2014 |
Publication |
Information Retrieval |
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IR |
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17 |
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5-6 |
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545-562 |
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Flowchart recognition; Patent documents; Text/graphics separation; Raster-to-vector conversion; Symbol recognition |
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Relatively little research has been done on the topic of patent image retrieval and in general in most of the approaches the retrieval is performed in terms of a similarity measure between the query image and the images in the corpus. However, systems aimed at overcoming the semantic gap between the visual description of patent images and their conveyed concepts would be very helpful for patent professionals. In this paper we present a flowchart recognition method aimed at achieving a structured representation of flowchart images that can be further queried semantically. The proposed method was submitted to the CLEF-IP 2012 flowchart recognition task. We report the obtained results on this dataset. |
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1386-4564 |
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DAG; 600.077 |
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no |
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Admin @ si @ RHR2013 |
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2342 |
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P. Ricaurte; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa |
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Title |
Performance Evaluation of Feature Point Descriptors in the Infrared Domain |
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Conference Article |
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2014 |
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9th International Conference on Computer Vision Theory and Applications |
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1 |
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545-550 |
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Infrared Imaging; Feature Point Descriptors |
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This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered. |
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Lisboa; Portugal; January 2014 |
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VISAPP |
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ADAS; 600.055; 600.076 |
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no |
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Admin @ si @ RCA2014b |
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2476 |
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Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Rendering ground truth data sets to detect shadows cast by static objects in outdoors |
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Journal Article |
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2014 |
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Multimedia Tools and Applications |
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MTAP |
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70 |
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1 |
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557-571 |
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Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection |
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In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically. |
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Springer US |
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1380-7501 |
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LAMP; |
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no |
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Admin @ si @ ISR2014 |
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2229 |
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Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone |
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Modelling task-dependent eye guidance to objects in pictures |
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Journal Article |
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2014 |
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Cognitive Computation |
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CoCom |
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6 |
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3 |
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558-584 |
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Visual attention; Gaze guidance; Value; Payoff; Stochastic fixation prediction |
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5Y Impact Factor: 1.14 / 3rd (Computer Science, Artificial Intelligence)
We introduce a model of attentional eye guidance based on the rationale that the deployment of gaze is to be considered in the context of a general action-perception loop relying on two strictly intertwined processes: sensory processing, depending on current gaze position, identifies sources of information that are most valuable under the given task; motor processing links such information with the oculomotor act by sampling the next gaze position and thus performing the gaze shift. In such a framework, the choice of where to look next is task-dependent and oriented to classes of objects embedded within pictures of complex scenes. The dependence on task is taken into account by exploiting the value and the payoff of gazing at certain image patches or proto-objects that provide a sparse representation of the scene objects. The different levels of the action-perception loop are represented in probabilistic form and eventually give rise to a stochastic process that generates the gaze sequence. This way the model also accounts for statistical properties of gaze shifts such as individual scan path variability. Results of the simulations are compared either with experimental data derived from publicly available datasets and from our own experiments. |
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Springer US |
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1866-9956 |
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DAG; 600.056; 600.045; 605.203; 601.212; 600.077 |
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Admin @ si @ CKL2014 |
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2419 |
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Permanent link to this record |
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Author |
A.Kesidis; Dimosthenis Karatzas |
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Title |
Logo and Trademark Recognition |
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Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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D |
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Pages |
591-646 |
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Keywords |
Logo recognition; Logo removal; Logo spotting; Trademark registration; Trademark retrieval systems |
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Abstract |
The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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no |
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Admin @ si @ KeK2014 |
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2425 |
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Author |
Naveen Onkarappa; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa |
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Title |
Cross-spectral Stereo Correspondence using Dense Flow Fields |
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Conference Article |
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Year |
2014 |
Publication |
9th International Conference on Computer Vision Theory and Applications |
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3 |
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613-617 |
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Keywords |
Cross-spectral Stereo Correspondence; Dense Optical Flow; Infrared and Visible Spectrum |
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Abstract |
This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach. |
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Lisboa; Portugal; January 2014 |
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VISAPP |
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Notes |
ADAS; 600.055; 600.076 |
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no |
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Call Number |
Admin @ si @ OAV2014 |
Serial |
2477 |
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