Essays about: "Disparity Estimation"

Showing result 1 - 5 of 16 essays containing the words Disparity Estimation.

  1. 1. Mobile-based 3D modeling : An indepth evaluation for the application to maintenance and supervision

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Martin De Pellegrini; [2021]
    Keywords : Computer Vision; 3D Reconstruction; Deep Learning; Indoor; Digital Twin; Point Cloud.; Datorsyn; 3Drekonstruktion; Deep Learning; inomhus; Digital Twin; Point Cloud.;

    Abstract : Indoor environment modeling has become a relevant topic in several applications fields including Augmented, Virtual and Mixed Reality. Furthermore, with the Digital Transformation, many industries have moved toward this technology trying to generate detailed models of an environment allowing the viewers to navigate through it or mapping surfaces to insert virtual elements in a real scene. READ MORE

  3. 2. Towards Visual-Inertial SLAM for Dynamic Environments Using Instance Segmentation and Dense Optical Flow

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Luis Alejandro Sarmiento Gonzalez; [2021]
    Keywords : Semantic SLAM; Stereo Vision; VisualInertial SLAM; Motion likelihood; Stereo disparity; Dense optical flow; Dynamic objects.; Semantisk SLAM; Stereo Vision; Visual-Inertial SLAM; Sannolikhet för rörelse; Stereoskillnader; Tätt optiskt flöde; Dynamiska objekt.;

    Abstract : Dynamic environments pose an open problem for the performance of visual SLAM systems in real-life scenarios. Such environments involve dynamic objects that can cause pose estimation errors. READ MORE

  4. 3. Inferring 3D trajectory from monocular data using deep learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Victor Sellstedt; [2021]
    Keywords : Deep Learning; Monocular trajectory estimation; Time series prediction; Synthetic data; Djupinlärning; Inferens från monkulära sekvenser; Tidsserieanalys; Syntetisk data;

    Abstract : Trajectory estimation, with regards to reconstructing a 3D trajectory from a 2D trajectory, is commonly achieved using stereo or multi camera setups. Although projections from 3D to 2D suffer significant information loss, some methods approach this problem from a monocular perspective to address limitations of multi camera systems, such as requiring points in to be observed by more than one camera. READ MORE

  5. 4. Correspondence-based pairwise depth estimation with parallel acceleration

    University essay from Mittuniversitetet/Avdelningen för informationssystem och -teknologi

    Author : Nadine Bartosch; [2018]
    Keywords : Depth estimation; disparity; stereo vision; stereo correspondence; NVIDIA; GPU; CUDA; parallelization;

    Abstract : This report covers the implementation and evaluation of a stereo vision corre- spondence-based depth estimation algorithm on a GPU. The results and feed- back are used for a Multi-view camera system in combination with Jetson TK1 devices for parallelized image processing and the aim of this system is to esti- mate the depth of the scenery in front of it. READ MORE

  6. 5. Deep Convolutional Neural Networks for Real-Time Single Frame Monocular Depth Estimation

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Jacob Schennings; [2017]
    Keywords : deep learning; machine learning; mono vision system; lightweight; CNN; convolutional neural network; depth estimation; lidar; kitti; vehicle camera; mono camera; camera; real-time; real time; ad; autonomous driving; adas; advanced driver assistance systems; mono depth; computer vision; regression; pixel-wise; pixel wise; object detection; general object detection; pedestrian detection; vehicle detection; supervised learning; supervised; tensorflow; python; keras; opencv; autoliv;

    Abstract : Vision based active safety systems have become more frequently occurring in modern vehicles to estimate depth of the objects ahead and for autonomous driving (AD) and advanced driver-assistance systems (ADAS). In this thesis a lightweight deep convolutional neural network performing real-time depth estimation on single monocular images is implemented and evaluated. READ MORE