Search results for "Computer Vision"
showing 10 items of 2353 documents
Laser Triangulation 3D Point Cloud Sensor with Long Range and Large Field of View
2020
This paper presents a point cloud sensor design based on laser triangulation. Both the camera axis and the laser axis are rotating, making it possible to scan on short and long range in high resolution. A third axis moves the laser and camera into a new plane. The design is tested on a working prototype. To the authors knowledge a similar design has not been presented before.
Integration of terrestrial laser scanning and UAV-SFM technique to generate a detailed 3D textured model of a heritage building
2020
The digital twin is among the Top 10 of the strategic technological trends for the period 2007-2019, and it represents a powerful tool for the conservation and enhancement of cultural heritage. It reproduces with "precision" a physical asset, thus allowing to investigate its structure and to analyze the deformations that occur over the years. Various techniques have been introduced to obtain high-resolution 3D models. Among these, the Terrestrial Laser Scanner (TLS) is widely recognized as the gold standard to generate accurate 3D metric reconstructions. TLS allows acquiring a lot of data (point cloud) in a fast way, being not in physical contact with the objects of investigation. By integr…
A Geometric Approach to Automatic Description of Iconic Scenes
2005
It is proposed a step towards the automatic description of scenes with a geometric approach. The scenes considered are composed by a set of elements that can be geometric forms or iconic representation of objects. Every icon is characterized by a set of attributes like shape, colour, position, orientation. Each scene is related to a set of sentences describing its content. The proposed approach builds a data driven vector semantic space where the scenes and the sentences are mapped. Sentences and scene with the same meaning are mapped in near vectors and distance criteria allow retrieving semantic relations.
Assessment of workflow feature selection on forest LAI prediction with sentinel-2A MSI, landsat 7 ETM+ and Landsat 8 OLI
2020
The European Space Agency (ESA)’s Sentinel-2A (S2A) mission is providing time series that allow the characterisation of dynamic vegetation, especially when combined with the National Aeronautics and Space Administration (NASA)/United States Geological Survey (USGS) Landsat 7 (L7) and Landsat 8 (L8) missions. Hybrid retrieval workflows combining non-parametric Machine Learning Regression Algorithms (MLRAs) and vegetation Radiative Transfer Models (RTMs) were proposed as fast and accurate methods to infer biophysical parameters such as Leaf Area Index (LAI) from these data streams. However, the exact design of optimal retrieval workflows is rarely discussed. In this study, the impact of…
Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments
2016
The task of designing estimators that are able to track time-varying distributions has found promising applications in many real-life problems.Existing approaches resort to sliding windows that track changes by discarding old observations. In this paper, we report a novel estimator referred to as the Stochastic Discretized Weak Estimator (SDWE), that is based on the principles of discretized Learning Automata (LA). In brief, the estimator is able to estimate the parameters of a time varying binomial distribution using finite memory. The estimator tracks changes in the distribution by operating a controlled random walk in a discretized probability space. The steps of the estimator are discre…
Review on Machine Learning Based Lesion Segmentation Methods from Brain MR Images
2016
Brain lesions are life threatening diseases. Traditional diagnosis of brain lesions is performed visually by neuro-radiologists. Nowadays, advanced technologies and the progress in magnetic resonance imaging provide computer aided diagnosis using automated methods that can detect and segment abnormal regions from different medical images. Among several techniques, machine learning based methods are flexible and efficient. Therefore, in this paper, we present a review on techniques applied for detection and segmentation of brain lesions from magnetic resonance images with supervised and unsupervised machine learning techniques.
Image boundaries detection: from thresholding to implicit curve evolution
2014
The development of high dimensional large-scale imaging devices increases the need of fast, robust and accurate image segmentation methods. Due to its intrinsic advantages such as the ability to extract complex boundaries, while handling topological changes automatically, the level set method (LSM) has been widely used in boundaries detection. Nevertheless, their computational complexity limits their use for real time systems. Furthermore, most of the LSMs share the limit of leading very often to a local minimum, while the effectiveness of many computer vision applications depends on the whole image boundaries. In this paper, using the image thresholding and the implicit curve evolution fra…
Architecture-Driven Level Set Optimization: From Clustering to Sub-pixel Image Segmentation
2016
Thanks to their effectiveness, active contour models (ACMs) are of great interest for computer vision scientists. The level set methods (LSMs) refer to the class of geometric active contours. Comparing with the other ACMs, in addition to subpixel accuracy, it has the intrinsic ability to automatically handle topological changes. Nevertheless, the LSMs are computationally expensive. A solution for their time consumption problem can be hardware acceleration using some massively parallel devices such as graphics processing units (GPUs). But the question is: which accuracy can we reach while still maintaining an adequate algorithm to massively parallel architecture? In this paper, we attempt to…
A local level set method for liver segmentation in functional MR imaging
2011
Functional Magnetic Resonance (fMR) is a medical image technique in which a contrast is injected in the vascular system so that blood diffusion along it can be observed as variations of the signal intensity. The uptake variations of the contrast agent are used in early detection of tumorous tissue. For the diagnostic to be accurate, successive volumes must be correctly registered. For binary registration prior segmentation of the 3D fMR data is required. Here we present a local 3D level-set segmentation method which preserves details and edges, along with its multi-scale version which has the advantage of a great acceleration with respect to the single-scale version. Results of liver segmen…
A LiDAR Prototype with Silicon Photomultiplier and MEMS Mirrors
2018
In this paper, we present a low cost prototype of a Time-Of-Flight (TOF) LiDAR system, employing a SiPM as photo detector and MEMS mirrors in order to steer the nanosecond pulsed optical beam with a scanning angle of +/-6°. Preliminary TOF measurements have been performed both indoor and outdoor to test the limits of the system.