Search results for "ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION"
showing 10 items of 982 documents
Gait Analysis Using Multiple Kinect Sensors
2014
A gait analysis technique to model user presences in an office scenario is presented in this chapter. In contrast with other approaches, we use unobtrusive sensors, i.e., an array of Kinect devices, to detect some features of interest. In particular, the position and the spatio-temporal evolution of some skeletal joints are used to define a set of gait features, which can be either static (e.g., person height) or dynamic (e.g., gait cycle duration). Data captured by multiple Kinects is merged to detect dynamic features in a longer walk sequence. The approach proposed here was been evaluated by using three classifiers (SVM, KNN, Naive Bayes) on different feature subsets.
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.
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.
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.
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.
Implementations of a novel algorithm for colour constancy
1997
AbstractIn agreement with the principles of the relativistic model proposed by Creutzfeldtet al., with the photometric rule (lightness anchoring rule) and with the influence of simultaneous contrast in the appearance of a visual scene, we propose a first-stage mechanism yielding substantial colour constancy. We have defined a set of first-stage colour descriptors, and to test their utility, we have performed a simulation using a Machine Vision System (MVS). The statistical stability of the descriptors for Munsell samples under different illuminants is good.
The problem of spatial homogeneity in an LCoS projector
2019
Abstract Video projectors allow interesting applications in vision sciences since they provide a large projection area. We have colorimetrically characterized a LCoS projector using a mathematical model requiring additivity and constancy of the primaries -a sigmoid function in our case. Significant differences in chromaticity in the CIELAB space, but not in lightness, were found between the center and the corners of the screen. The lack of spatial homogeneity led us to estimate the parameters of the model as a function of spatial position, using different strategies. The best result was obtained by interpolating the values of the parameters of the model determined from experimental measurem…
Eye tracking and the translation process: reflections on the analysis and interpretation of eye-tracking data
2014
Eye tracking has become increasingly popular as a quantitative research method in translation research. This paper discusses some of the major methodological issues involved in the use of eye tracking in translation research. It focuses specifically on challenges in the analysis and interpretation of eye-tracking data as reflections of cognitive processes during translation. Four types of methodological issues are discussed in the paper. The first part discusses the preparatory steps that precede the actual recording of eye-tracking data. The second part examines critically the general assumptions linking eye movements to cognitive processing in the context of translation research. The thir…
Collaborative Virtual Reality for Laparoscopic Liver Surgery Training
2019
Virtual reality (VR) has been used in many medical training systems for surgical procedures. However, the current systems are limited due to inadequate interactions, restricted possibilities of patient data visualization, and collaboration. We propose a collaborative VR system for laparoscopic liver surgical planning and simulation. Medical image data is used for model visualization and manipulation. Additionally, laparoscopic surgical joysticks are used to provide an opportunity for a camera assistant to cooperate with an experienced surgeon in VR. Continuous clinical feedback led us to optimize the visualization, synchronization, and interactions of the system. Laparoscopic surgeons were …
A collaborative virtual reality environment for liver surgery planning
2021
Abstract Surgical planning software is a key component in the treatment of tumor diseases. However, desktop-based systems provide only limited visualization and interaction opportunities. Moreover, collaborative planning among members of a surgical team is only possible to a limited extent. In this work, a collaborative virtual reality (VR) environment to assist liver surgeons in tumor surgery planning is presented. Our aim is to improve virtual resection planning between surgeons in a remote or co-located environment. The system allows surgeons to define and adjust virtual resections on patient-specific organ 3D surfaces and 2D image slices. Changes on both modalities are synchronized, whi…