Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance o...Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.展开更多
The measurement of the surface quality and the profile preciseness is major issues in many industrial branches such that the surface quality of semi products directly affects the subsequent production steps.Although,t...The measurement of the surface quality and the profile preciseness is major issues in many industrial branches such that the surface quality of semi products directly affects the subsequent production steps.Although,there are many ways to obtain required data,the hardware necessary for the measurements such as 2D or 3D scanners,depending on the problem’s complexity,is too expensive.Therefore,in this paper,what we put forward as a novelty is an algorithm which is verified on the model of simple 3D scanner on the image processing basis with the resolution of 0.1 mm.There are many ways to scan surface profile;however,the image processing currently is the most trending topic in industry automation.Most importantly,in order to obtain surface images,standard high resolution reflex camera is used and thus the post processing could be realized with MatLab as the software environment.Therefore,this solution is an alternative to the expensive scanners,and single-purpose devices could be extended by many additional functions.展开更多
文摘Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.
基金Project(2102–2020)supported by the SPEV Project,University of Hradec Kralove,FIM,Czech RepublicProject(Vot-20H04)supported by Universiti Teknologi Malaysia(UTM)+1 种基金Project(Vot 4L876)supported by Malaysia Research University Network(MRUN)Project(Vot 5F073)supported by the Fundamental Research Grant Scheme(FRGS),Ministry of Education Malaysia。
文摘The measurement of the surface quality and the profile preciseness is major issues in many industrial branches such that the surface quality of semi products directly affects the subsequent production steps.Although,there are many ways to obtain required data,the hardware necessary for the measurements such as 2D or 3D scanners,depending on the problem’s complexity,is too expensive.Therefore,in this paper,what we put forward as a novelty is an algorithm which is verified on the model of simple 3D scanner on the image processing basis with the resolution of 0.1 mm.There are many ways to scan surface profile;however,the image processing currently is the most trending topic in industry automation.Most importantly,in order to obtain surface images,standard high resolution reflex camera is used and thus the post processing could be realized with MatLab as the software environment.Therefore,this solution is an alternative to the expensive scanners,and single-purpose devices could be extended by many additional functions.
