During the past decade, localization microscopy (LM) has transformed into an accessible, commercially available technique for life sciences. However, data processing can be challenging to the non-specialist and care i...
详细信息
During the past decade, localization microscopy (LM) has transformed into an accessible, commercially available technique for life sciences. However, data processing can be challenging to the non-specialist and care is still needed to produce meaningful results. PALMsiever has been developed to provide a user-friendly means of visualizing, filtering and analyzing LM data. It includes drift correction, clustering, intelligent line profiles, many rendering algorithms and 3D data visualization. It incorporates the main analysis and data processing modalities used by experts in the field, as well as several new features we developed, and makes them broadly accessible. It can easily be extended via plugins and is provided as free of charge open-source software.
images remain the most popular medium to capture our surroundings. Although significant advances have been made in developing image editing tools, the key challenge is to intelligently account for missing depth inform...
详细信息
images remain the most popular medium to capture our surroundings. Although significant advances have been made in developing image editing tools, the key challenge is to intelligently account for missing depth information. The growing popularity of depth images offers a new avenue to revisit image editing tasks. In this work, we investigate how even coarse depth information can be exploited to address some of the fundamental challenges in image editing namely producing correct perspective, handling occlusion, and obtaining segmentation. To this end, we propose a novel image degradation model that predicts how well an image edit can be performed in presence of coarse depth information. Technically, we create proxy geometry to summarize available depth information, and use it to predict occlusions and ordering between image patches, complete occluded regions, and anticipate image-level changes under camera movement. We evaluate the proposed image degradation model in the context of parallax photography from single depth images.
This work introduces MetaTracts, a novel method for extracting and visualizing individual fiber bundles and weaving patterns from X-ray computed tomography (XCT) scans of endless carbon fiber reinforced polymers (CFRP...
详细信息
ISBN:
(纸本)9781467368797
This work introduces MetaTracts, a novel method for extracting and visualizing individual fiber bundles and weaving patterns from X-ray computed tomography (XCT) scans of endless carbon fiber reinforced polymers (CFRP). The proposed work flow is designed to analyze unit cells of CFRP materials integrating the recurring weaving pattern. It is designed to handle XCT scans of low resolution, in which individual fibers are not visible or are barely visible. First, a coarse version of integral curves is used to trace subsections of the individual fiber bundles in the woven CFRP materials. We call these sections MetaTracts. In the second step, these extracted fiber bundle sections (MetaTracts) are clustered using a two-step approach: first by orientation, then by proximity. The tool can generate volumetric representations as well as surface models of the extracted fiber bundles to be exported for further analysis. We evaluate the proposed work flow on a number of real world datasets and demonstrate that MetaTracts effectively and robustly identifies and separates different fiber bundles.
SemVisM is a toolbox that combines medical informatics and computergraphics tools for reducing the semantic gap between low-level features and high-level semantic concepts/terms in the images. This paper presents a n...
详细信息
ISBN:
(纸本)9781628413625
SemVisM is a toolbox that combines medical informatics and computergraphics tools for reducing the semantic gap between low-level features and high-level semantic concepts/terms in the images. This paper presents a novel strategy for visualizing medical data annotated semantically, combining rendering techniques, and segmentation algorithms. SemVisM comprises two main components: i) AMORE (A Modest vOlume REgister) to handle input data (RAW, DAT or DICOM) and to initially annotate the images using terms defined on medical ontologies (e.g., MesH, FMA or RadLex), and ii) VOLPROB (VOlume PRObability Builder) for generating the annotated volumetric data containing the classified voxels that belong to a particular tissue. SemVisM is built on top of the semantic visualizer ANISE.(1)
Detecting changes in scenes is important in many scene understanding tasks. In this paper, we pursue this goal simply from a pair of image recordings. Specifically, our goal is to infer what the objects are, how they ...
详细信息
Detecting changes in scenes is important in many scene understanding tasks. In this paper, we pursue this goal simply from a pair of image recordings. Specifically, our goal is to infer what the objects are, how they are structured, and how they moved between the images. The problem is challenging as large changes make point-level correspondence establishment difficult, which in turn breaks the assumptions of standard Structure-from-Motion (SfM). We propose a novel algorithm for dynamic SfM wherein we first generate a pool of potential corresponding points by hypothesizing over possible movements, and then use a continuous optimization formulation to obtain a low complexity solution that best explains the scene recordings, i.e., the input image pairs. We test the algorithm on a variety of examples to recover the multiple object structures and their changes.
The improvement of digital cameras and computers' processing capabilities have made applicable the solutions of a wide range of problems regarding imageprocessing and computer vision. Among the most interesting t...
详细信息
The improvement of digital cameras and computers' processing capabilities have made applicable the solutions of a wide range of problems regarding imageprocessing and computer vision. Among the most interesting tasks in this field of expertise, there are several face related problems. Many works have been proposed to solve problems such as face recognition, expression and age estimation, facial reconstruction, etc. Those works have a large potential to be explored in applications ranging from computergraphics to security and, even, medical software. This work proposes a method to automatic locate and identify a set of facial landmarks. The goal is to quickly provide precise and helpful information for plastic surgery procedures. The proposal, after implemented and tested on over 400 images, presented encouraging results for aesthetic analysis. Besides, it brings a novel methodology to locating specific landmarks needed for planning surgeries.
We present an adaptive integration strategy to evaluate the volume rendering integral for regular volumes. We discuss different strategies to control the step size for both the inner and the outer integrals in the vol...
详细信息
We present an adaptive integration strategy to evaluate the volume rendering integral for regular volumes. We discuss different strategies to control the step size for both the inner and the outer integrals in the volume rendering equation. We report a set of computational experiments that compare both accuracy and efficiency of our proposal against Riemann summation with uniform step size. The comparisons are made for both CPU and GPU implementations and show that our method delivers both accuracy control and competitive performance.
This paper aims at describing an approach developed for the recognition of gestures on digital images. In this way, two shape descriptors were used: the histogram of oriented gradients (HOG) and Zernike invariant mome...
详细信息
This paper aims at describing an approach developed for the recognition of gestures on digital images. In this way, two shape descriptors were used: the histogram of oriented gradients (HOG) and Zernike invariant moments (ZIM). A feature vector composed by the information acquired with both descriptors was used to train and test a two stage Neural Network, which is responsible for performing the recognition. In order to evaluate the approach in a practical context, a dataset containing 9600 images representing 40 different gestures (signs) from brazilian Sign Language (Libras) was composed. This approach showed high recognition rates (hit rates), reaching a final average of 96.77%.
Facial expression recognition has been an active research area in the past ten years, with a growing application area like avatar animation and neuromarketing. The recognition of facial expressions is not an easy prob...
详细信息
Facial expression recognition has been an active research area in the past ten years, with a growing application area like avatar animation and neuromarketing. The recognition of facial expressions is not an easy problem for machine learning methods, since different people can vary in the way that they show their expressions. And even an image of the same person in one expression can vary in brightness, background and position. Therefore, facial expression recognition is still a challenging problem in computer vision. In this work, we propose a simple solution for facial expression recognition that uses a combination of standard methods, like Convolutional Network and specific image pre-processing steps. Convolutional networks, and the most machine learning methods, achieve better accuracy depending on a given feature set. Therefore, a study of some image pre-processing operations that extract only expression specific features of a face image is also presented. The experiments were carried out using a largely used public database for this problem. A study of the impact of each image pre-processing operation in the accuracy rate is presented. To the best of our knowledge, our method achieves the best result in the literature, 97.81% of accuracy, and takes less time to train than state-of-the-art methods.
Although light fields are well-established as a tool in image-based rendering and computer vision, their capture is still at a relatively early stage. In this article, we search for imaging situations similar to uncal...
详细信息
暂无评论