|
|
Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2011). A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth. In IEEE International Conference on Computer Vision – Workshops (pp. 2042–2049). Barcelona (Spain): IEEE.
Abstract: Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems.
Keywords: IEEE International Conference on Computer Vision – Workshops
|
|
|
|
Sezer Karaoglu, Jan van Gemert, & Theo Gevers. (2013). Con-text: text detection using background connectivity for fine-grained object classification. In 21ST ACM International Conference on Multimedia (pp. 757–760).
|
|
|
|
Marina Alberti, Carlo Gatta, Simone Balocco, Francesco Ciompi, Oriol Pujol, Joana Silva, et al. (2011). Automatic Branching Detection in IVUS Sequences. In Jordi Vitria, Joao Miguel Raposo, & Mario Hernandez (Eds.), 5th Iberian Conference on Pattern Recognition and Image Analysis (Vol. 6669, pp. 126–133). LNCS. Berlin: Springer Berlin Heidelberg.
Abstract: Atherosclerosis is a vascular pathology affecting the arterial walls, generally located in specific vessel sites, such as bifurcations. In this paper, for the first time, a fully automatic approach for the detection of bifurcations in IVUS pullback sequences is presented. The method identifies the frames and the angular sectors in which a bifurcation is visible. This goal is achieved by applying a classifier to a set of textural features extracted from each image of an IVUS pullback. A comparison between two state-of-the-art classifiers is performed, AdaBoost and Random Forest. A cross-validation scheme is applied in order to evaluate the performances of the approaches. The obtained results are encouraging, showing a sensitivity of 75% and an accuracy of 94% by using the AdaBoost algorithm.
|
|
|
|
Antonio Hernandez, Carlo Gatta, Laura Igual, Sergio Escalera, & Petia Radeva. (2011). Automatic Angiography Segmentation Based on Improved Graph-cut. In Jornada TIC Salut Girona.
|
|
|
|
Laura Igual, Antonio Hernandez, Sergio Escalera, Miguel Reyes, Josep Moya, Joan Carles Soliva, et al. (2011). Automatic Techniques for Studying Attention-Deficit/Hyperactivity Disorder. In Jornada TIC Salut Girona.
|
|
|
|
Francesco Ciompi, Oriol Pujol, Simone Balocco, Xavier Carrillo, J. Mauri, & Petia Radeva. (2011). Automatic Key Frames Detection in Intravascular Ultrasound Sequences. In In MICCAI 2011 Workshop on Computing and Visualization for Intra Vascular Imaging.
Abstract: We present a method for the automatic detection of key frames in Intravascular Ultrasound (IVUS) sequences. The key frames are markers delimiting morphological changes along the vessel. The aim of defining key frames is two-fold: (1) they allow to summarize the content of the pullback into few representative frames; (2) they represent the basis for the automatic detection of clinical events in IVUS. The proposed approach achieved a compression ratio of 0.016 with respect to the original sequence and an average inter-frame distance of 61.76 frame, minimizing the number of missed clinical events.
|
|
|
|
Miguel Angel Bautista, Sergio Escalera, Xavier Baro, Oriol Pujol, Jordi Vitria, & Petia Radeva. (2010). Compact Evolutive Design of Error-Correcting Output Codes. Supervised and Unsupervised Ensemble Methods and Applications. In European Conference on Machine Learning (Vol. I, pp. 119–128).
|
|
|
|
Simone Balocco, Carlo Gatta, Xavier Carrillo, J. Mauri, & Petia Radeva. (2011). Plaque Type, Plaque Burden and Wall Shear Stress Relation in Coronary Arteries Assessed by X-ray Angiography and Intravascular Ultrasound: a Qualitative Study. In 14th International Symposium on Applied Sciences in Biomedical and Communication Technologies.
Abstract: In this paper, we present a complete framework that automatically provides fluid-dynamic and plaque analysis from IVUS and Angiographic sequences. Such framework is used to analyze, in three coronary arteries, the relation between wall shear stress with type and amount of plaque. Preliminary qualitative results show an inverse relation between the wall shear stress and the plaque burden, which is confirmed by the fact that the plaque growth is higher on the wall having concave curvature. Regarding the plaque type it was observed that regions having low shear stress are predominantly fibro-lipidic while the heavy calcifications are in general located in areas of the vessel having high WSS.
|
|
|
|
Lluis Pere de las Heras, Joan Mas, Gemma Sanchez, & Ernest Valveny. (2011). Descriptor-based Svm Wall Detector. In 9th International Workshop on Graphic Recognition.
Abstract: Architectural floorplans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. In this paper we describe an evolution of this new approach in two directions: firstly we evaluate different features to obtain the description of every patch. Secondly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These modifications of the method have been tested for wall detection on two datasets of architectural floorplans with different notations and compared with the results obtained with the original approach.
|
|
|
|
Alicia Fornes, Volkmar Frinken, Andreas Fischer, Jon Almazan, G. Jackson, & Horst Bunke. (2011). A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors. In Proceedings of the 2011 Workshop on Historical Document Imaging and Processing (pp. 83–90). ACM.
Abstract: The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach.
|
|
|
|
Andreas Fischer, Volkmar Frinken, Alicia Fornes, & Horst Bunke. (2011). Transcription Alignment of Latin Manuscripts Using Hidden Markov Models. In Proceedings of the 2011 Workshop on Historical Document Imaging and Processing (pp. 29–36). ACM.
Abstract: Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models.
|
|
|
|
S.Grau, Ana Puig, Sergio Escalera, & Maria Salamo. (2013). Intelligent Interactive Volume Classification. In Pacific Graphics (Vol. 32, pp. 23–28).
Abstract: This paper defines an intelligent and interactive framework to classify multiple regions of interest from the original data on demand, without requiring any preprocessing or previous segmentation. The proposed intelligent and interactive approach is divided in three stages: visualize, training and testing. First, users visualize and label some samples directly on slices of the volume. Training and testing are based on a framework of Error Correcting Output Codes and Adaboost classifiers that learn to classify each region the user has painted. Later, at the testing stage, each classifier is directly applied on the rest of samples and combined to perform multi-class labeling, being used in the final rendering. We also parallelized the training stage using a GPU-based implementation for
obtaining a rapid interaction and classification.
|
|
|
|
G.D. Evangelidis, Ferran Diego, Joan Serrat, & Antonio Lopez. (2011). Slice Matching for Accurate Spatio-Temporal Alignment. In In ICCV Workshop on Visual Surveillance.
Abstract: Video synchronization and alignment is a rather recent topic in computer vision. It usually deals with the problem of aligning sequences recorded simultaneously by static, jointly- or independently-moving cameras. In this paper, we investigate the more difficult problem of matching videos captured at different times from independently-moving cameras, whose trajectories are approximately coincident or parallel. To this end, we propose a novel method that pixel-wise aligns videos and allows thus to automatically highlight their differences. This primarily aims at visual surveillance but the method can be adopted as is by other related video applications, like object transfer (augmented reality) or high dynamic range video. We build upon a slice matching scheme to first synchronize the sequences, while we develop a spatio-temporal alignment scheme to spatially register corresponding frames and refine the temporal mapping. We investigate the performance of the proposed method on videos recorded from vehicles driven along different types of roads and compare with related previous works.
Keywords: video alignment
|
|
|
|
Fahad Shahbaz Khan, Joost Van de Weijer, Andrew Bagdanov, & Maria Vanrell. (2011). Portmanteau Vocabularies for Multi-Cue Image Representation. In 25th Annual Conference on Neural Information Processing Systems.
Abstract: We describe a novel technique for feature combination in the bag-of-words model of image classification. Our approach builds discriminative compound words from primitive cues learned independently from training images. Our main observation is that modeling joint-cue distributions independently is more statistically robust for typical classification problems than attempting to empirically estimate the dependent, joint-cue distribution directly. We use Information theoretic vocabulary compression to find discriminative combinations of cues and the resulting vocabulary of portmanteau words is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. State-of-the-art results on both the Oxford Flower-102 and Caltech-UCSD Bird-200 datasets demonstrate the effectiveness of our technique compared to other, significantly more complex approaches to multi-cue image representation
|
|
|
|
Naila Murray, Sandra Skaff, Luca Marchesotti, & Florent Perronnin. (2011). Towards Automatic Concept Transfer. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering (167.176). ACM Press.
Abstract: This paper introduces a novel approach to automatic concept transfer; examples of concepts are “romantic”, “earthy”, and “luscious”. The approach modifies the color content of an input image given only a concept specified by a user in natural language, thereby requiring minimal user input. This approach is particularly useful for users who are aware of the message they wish to convey in the transferred image while being unsure of the color combination needed to achieve the corresponding transfer. The user may adjust the intensity level of the concept transfer to his/her liking with a single parameter. The proposed approach uses a convex clustering algorithm, with a novel pruning mechanism, to automatically set the complexity of models of chromatic content. It also uses the Earth-Mover's Distance to compute a mapping between the models of the input image and the target chromatic concept. Results show that our approach yields transferred images which effectively represent concepts, as confirmed by a user study.
Keywords: chromatic modeling, color concepts, color transfer, concept transfer
|
|
