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Superpixel-Based Interactive Classification of Very High Resolution images

Superpixel-Based Interactive Classification of Very High Res...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： John E. Vargas Priscila T. M. Saito Alexandre X. Falcao Pedro J. De Rezende Jefersson A. Dos Santos Institute of Computing University of Campinas Campinas Brazil Federal Technological University of Parana Cornelio Procopio Brazil Inst. of Comput. Universidade Estadual de Campinas Campinas SP BR Universidade Federal de Minas Gerais Belo Horizonte MG BR

ISBN: (纸本)9781479942572

Very high resolution (VHR) images are large datasets for pixel annotation -- a process that has depended on the supervised training of an effective pixel classifier. Active learning techniques have mitigated this problem, but pixel descriptors are limited to local image information and the large number of pixels makes the response time to the user's actions impractical, during active learning. To circumvent the problem, we present an active learning strategy that relies on superpixel descriptors and a priori dataset reduction. Firstly, we compare VHR image annotation using superpixel- and pixel-based classifiers, as designed by the same state-of-the-art active learning technique -- Multi-Class Level Uncertainty (MCLU). Even with the dataset reduction provided by the superpixel representation, MCLU remains unfeasible for user interaction. therefore, we propose a technique to considerably reduce the superpixel dataset for active learning. Moreover, we subdivide the reduced dataset into a list of subsets with random sample rearrangement to gain both speed and sample diversity during the active learning process.

关键词： Training Uncertainty image color analysis Accuracy Clustering algorithms Support vector machines Histograms

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Graph Based Characterization of Microcirculation in Sepsis Using Sidestream Dark Field Imaging

Graph Based Characterization of Microcirculation in Sepsis U...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： J. M. Zoghbi L. T. De-La-Cruz M. A. G. V. Galarreta Marcel P. Jackowski J. C. F. Vieira A. M. A. Liberatore Ivan H. J. Koh Inst. of Math. & Stat. Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR Inst. of Math. & Stat Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR Institute of Mathematics and Statistics University of São Paulo São Paulo Brazil Universidade Federal de Sao Paulo Sao Paulo SÃ£o Paulo BR

Real-time detection of sepsis on a video data is a new aboard technique that aids the septic patient and decreases the high mortality rate. the progressive impairment of the micro-circulation associated with increased systemic inflammatory response in sepsis has been considered the origin of the multiple organ dysfunction syndrome that often leads to death. However, despite the recognized importance of the micro-circulatory dysfunction, analysis methods able to correlate the severity of sepsis with the degree of impairment of micro-hemodynamic captured by portable microscope Side-stream Dark Field Imaging (SDF) are rarely used. Hence, the classification of the severity of sepsis by analyzing the micro-circulatory dysfunction would be of great assistance in diagnosing severity and therapeutic management. In this context, the aim of this work is to propose a new computational methodology based on image processing to obtain graph metrics for determining the degree of micro-vascular and tissue commitment due to sepsis.

关键词： Taxonomy Blood vessels Biomedical imaging image edge detection Mice image segmentation

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Improving On-Patient Medical Data Visualization in a Markerless Augmented Reality Environment by Volume Clipping

Improving On-Patient Medical Data Visualization in a Markerl...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Marcio Cerqueira de Farias Macedo Antonio Lopes Apolinario Federal University of Bahia (UFBA) Bahia Brazil Universidade Federal da Bahia Salvador BA BR

To improve the human perception of an augmented reality scene, its virtual and real entities can be rendered according to the focus+context visualization. this paradigm is specially important in the field of on-patient medical data visualization, as it provides insight to the physicians about the spatial relations between the patient's anatomy (focus region) and his entire body (context region). However, the current existing methods proposed in this field do not give special treatment to the effect of volume clipping, which can open new ways for physicians to explore and understand the entire scene. In this paper we introduce an on-patient focus+context medical data visualization based on volume clipping. It is proposed in a markerless augmented reality environment. From the estimated camera pose, the volumetric medical data can be displayed to a physician inside the patient's anatomy at the location of the real anatomy. To improve the visual quality of the final scene, three methods based on volume clipping are proposed to allow new focus+context visualizations. Moreover, the whole solution supports occlusion handling. From the evaluation of the proposed techniques, the results obtained highlight that these methods improve the visual quality of the final rendering. Furthermore, the application still runs in realtime.

关键词： Data visualization three-dimensional displays Solid modeling Rendering (computer graphics) Context Medical diagnostic imaging

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Portable Digital in-Line Holography Platform for Sperm Cell Visualization and Quantification

Portable Digital in-Line Holography Platform for Sperm Cell ...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Antonio Carlos Sobieranski Fatih Inci H. Cumhur Tekin Eros Comunello Aldo Von Wangenheim Utkan Demirci Department of Medicine Harvard Medical School Boston MA US Department of Informatics Federal University of Parana Brazil Med. Sch. Center for Biomed. Eng. Harvard Medical School Boston MA US INCoD - National Brazilian Institute for Digital Convergence Federal University of Santa Catarina Brazil Universidade Federal do Parana Curitiba PR BR Harvard-MIT Health Sciences and Technology Division Massachusetts Institute of Technology Cambridge MA US

ISBN: (纸本)9781479942572

In this paper a new portable Digital In-line Holography Platform for biological micro-scale imaging of sperm samples is presented. this platform is based on the shadow imaging principle, where biological samples are illuminated by a nearly coherent light source, and shadows are recorded into a CMOS imaging sensor with no lens requirement. the projected shadows present holographic signatures, storing more than bidimensional information of the analyzed sample. To improve resolution and suppress noise of the acquired holograms, a multi-frame technique based on high-dynamic range imaging combined with summation of consecutive frames over time was used. Finally, decoding of holograms is performed by an efficient and fast phase-recovery method, where morphological details of the sample can be obtained similarly a conventional brightfield microscopy image. From an image formation point of view, the proposed portable approach is able to visualize biological samples in high synthetic numerical aperture values with a spatial resolution of 1-2 μm on a field-of-view of ≈30 mm 2 . this field-of-view is consistently bigger than a conventional microscope imaged area with no mosaic reconstruction, and the achieved resolution is obtained using a single illumination source with no moving parts, array of LEDs or sift of the light source. Validation of the proposed portable approach was performed using various human samples, where conventional microscopy was used for confirmation purposes.

关键词： Visualization Biology Microscopy image resolution Noise Diffraction

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Learning to Annotate Clothes in Everyday Photos: Multi-modal, Multi-label, Multi-instance Approach

Learning to Annotate Clothes in Everyday Photos: Multi-modal...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Adriano Alonso Veloso Jefersson A. Dos Santos Keiller Nogueira Universidade Federal de Minas Gerais Belo Horizonte Brazil Universidade Federal de Minas Gerais Belo Horizonte MG BR

ISBN: (纸本)9781479942572

In this paper, we present an effective algorithm to automatically annotate clothes in everyday photos posted in online social networks, such as Facebook and Instagram. Specifically, clothing annotation can be informally stated as predicting, as accurately as possible, the garment items appearing in the target photo. this task not only poses interesting challenges for existing vision and recognition algorithms, but also brings huge opportunities for recommender and e-commerce systems. We formulate the annotation task as a multi-modal, multi-label and multi-instance classification problem: (i) both image and textual content (i.e., comments about the image) are available for learning classifiers, (ii) the classifiers must predict a set of labels (i.e., a set of garment items), and (iii) the decision on which labels to predict comes from a bag of instances that are used to build a function, which separates labels that should be predicted from those that should not be. Under this setting, we propose a classification algorithm which employs association rules in order to build a prediction model that combines image and textual information, and adopts an entropy-minimization strategy in order to the find the best set of labels to predict. We conducted a systematic evaluation of the proposed algorithm using everyday photos collected from two major fashion-related social networks, namely *** and ***. Our results show that the proposed algorithm provides improvements when compared to popular first choice multi-label algorithms that range from 2% to 40% in terms of accuracy.

关键词： Clothing Prediction algorithms Entropy Visualization image color analysis Social network services Feature extraction

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Fuzzy Inference Methods Applied to the Learning Competence Measure in Dynamic Classifier Selection

Fuzzy Inference Methods Applied to the Learning Competence M...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Marek Kurzynski Maciej Krysmann Department of Systems and Computer Networks Wroclaw University of Technology Wroclaw Poland

ISBN: (纸本)9781479942572

the concept of classifier competence in the feature space is fundamental to dynamic classifier selection in multiple classifier systems (MCS). Competence function (measure) of base classifier can be determined using validation set in the two step procedure. the first step consists in creating competence set, i.e. the set of classifier competences for all validation objects. To this end a hypothetical classifier called randomized reference classifier (RRC) is constructed. Since RRC - on average - acts like the evaluated classifier, the competence of the classifier at validation point is calculated as the probability of correct classification at this point of the respective RRC. In the second step, the competences calculated for a validation set are generalised to an entire feature space by constructing a competence function based on a supervised learning procedure. In this study, the second step of the above procedure is addressed by developing the fuzzy inference methods of learning competence functions. Two fuzzy inference systems are developed and applied to the supervised learning competence function of base classifiers in a MCS system with dynamic classifier selection (DCS) and dynamic ensemble selection (DES) scheme: Mamdani fuzzy inference system and Sugeno fuzzy inference system. Both fuzzy inference systems were experimentally tested and compared against 4 literature methods of learning classifier competence (potential function, regression model, multilayer perceptron, k-nearest neighbor scheme) using 9 databases taken from the UCI Machine Learning Repository. the experimental results clearly show the effectiveness of the proposed supervised learning competence function using fuzzy inference systems regardless of the ensemble type used (homogeneous or heterogeneous).

关键词： Fuzzy logic Vectors Supervised learning Probability Fuzzy sets Pragmatics Testing

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Improvement of texture based image segmentation algorithm for HE stained tissue samples

Improvement of texture based image segmentation algorithm fo...

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14th IEEE International symposium on Computational Intelligence and Informatics (CINTI)

作者： Windisch, G. Kozlovszky, M. Obuda Univ John von Neumann Fac Informat Budapest Hungary

ISBN: (纸本)9781479901944;9781479901975

Superpixel algorithms are becoming a widely used method for many computer vision applications, and it could be used as a basis of image segmentation for digital microscopy images of HE stained tissue samples. Research results show that among the many superpixel methods SLIC yields the best results when it comes to boundary adherence accuracy for normal images. In an effort to find out if it can be used for segmenting tissue images we have devised a benchmark to measure the performance of SLIC and tried improving the performance by careful tuning of the parameters to better fit SLIC to our special image processing needs.

关键词： Superpixels tissue sample segmentation SLIC

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Extraction of numerical residues in families of levelings

Extraction of numerical residues in families of levelings

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2013 26th Conference on graphics, Patterns and images, SIBGRAPI 2013

作者： Alves, Wonder Alexandre Luz Morimitsu, Alexandre Castro, Joel Sanchez Hashimoto, Ronaldo Fumio Department of Computer Science Institute of Mathematics and Statistics University of Sao Paulo Sao Paulo Brazil

ISBN: (纸本)9780769550992

this work introduces a residual operator called ultimate attribute leveling. We also present an efficient algorithm for ultimate attribute leveling computation by using a structure called tree of shapes. Our algorithm for computating ultimate attribute leveling is based on the fact (proved in this work) that levelings can be obtained by pruning nodes from the tree of shapes. this is a novel result, since so far it is known that levelings can be obtained from component trees. Finally, we propose the use of ultimate attribute leveling with shape information to extract contrast using a priori knowledge of an application. Experimental results applied to text location show the potentiality of using ultimate attribute leveling with shape information for solving problems in image processing area. © 2013 IEEE.

关键词： image processing

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Parallel image segmentation using reduction-sweeps on multicore processors and GPUs

Parallel image segmentation using reduction-sweeps on multic...

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2013 26th Conference on graphics, Patterns and images, SIBGRAPI 2013

作者： Farias, Renato Farias, Ricardo Marroquim, Ricardo Clua, Esteban Programa de Engenharia de Sistemas de Computacao Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Instituto de Computacao Universidade Federal Fluminense Niteroi Brazil

ISBN: (纸本)9780769550992

In this paper we introduce the Reduction Sweep algorithm, a novel graph-based image segmentation algorithm that is designed for easy parallelization. It is based on a clustering approach focusing on local image characteristics. Each pixel is compared with its neighbors in an implicitly independent manner, and those deemed sufficiently similar according to a color criterion are joined. We achieve fast execution times while still maintaining the visual quality of the results. the algorithm is presented in four different implementations: sequential CPU, parallel CPU, GPU, and hybrid CPU-GPU. We compare the execution times of the four versions with each other and with other closely related image segmentation algorithms. © 2013 IEEE.

关键词： graphics processing unit

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Realistic modeling of self-adapted spider orb-webs in real-time

Realistic modeling of self-adapted spider orb-webs in real-t...

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2013 26th Conference on graphics, Patterns and images, SIBGRAPI 2013

作者： Schmitt, Wagner Walter, Marcelo Comba, Joao Luiz Dihl Instituto de Informatica UFRGS Porto Alegre Brazil

ISBN: (纸本)9780769550992

Modeling organic objects and natural phenomena is a very time consuming task, and usually requires a certain level of expertise. this happens due to the lack of suitable geometric primitives available in most modeling tools. In addition, with the great advance in real-time rendering power, there is a growing demand for more complex models. Hence, this paper proposes a method to automatically build visually convincing spider orb-webs that are self-adapted to the environment. We show results of mesh-based spider orb-webs built in real-time that are visually pleasing and realistically looking. © 2013 IEEE.

关键词： Rendering (computer graphics)

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