Real-Time Dynamic Object Recognition and Grasp Detection for Robotic Arm using Streaming Video: A Design for Visually Impaired Persons

2021 ◽  
Author(s):  
Francis Liri ◽  
Henry Lin ◽  
Kayla Lee ◽  
Brian Fonseca ◽  
Nate Ruppert ◽  
...  
Keyword(s):  
Object Recognition ◽  
Real Time ◽  
Visually Impaired ◽  
Streaming Video ◽  
Robotic Arm ◽  
Dynamic Object ◽  
Time Dynamic ◽  
Visually Impaired Persons

scholarly journals A 320 mW 342 GOPS Real-Time Dynamic Object Recognition Processor for HD 720p Video Streams

2013 ◽  
Vol 48 (1) ◽  
pp. 33-45 ◽  
Author(s):  
Jinwook Oh ◽  
Gyeonghoon Kim ◽  
Junyoung Park ◽  
Injoon Hong ◽  
Seungjin Lee ◽  
...  
Keyword(s):  
Object Recognition ◽  
Real Time ◽  
Dynamic Object ◽  
Video Streams ◽  
Time Dynamic

scholarly journals Real-Time Dynamic Object Detection for Autonomous Driving Using Prior 3D-Maps

2019 ◽  
pp. 567-582 ◽  
Author(s):  
B. Ravi Kiran ◽  
Luis Roldão ◽  
Beñat Irastorza ◽  
Renzo Verastegui ◽  
Sebastian Süss ◽  
...  
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Autonomous Driving ◽  
Dynamic Object ◽  
Time Dynamic

scholarly journals Recognition and Location Estimation for Multiple Indoor Static Objects

2019 ◽  
Vol 8 (2) ◽  
pp. 5152-5156
Keyword(s):  
Support Vector Machine ◽  
Real Time ◽  
Visually Impaired ◽  
Location Estimation ◽  
Support Vector ◽  
Robotic Navigation ◽  
Image Objects ◽  
Sift Features ◽  
Adaboost Classifier ◽  
Visually Impaired Persons

Locating objects in an image is a very useful task for robotic navigation and visually impaired persons. The ultimate goal of my work is to position the recognized objects in the image. Objects are detected using Adaboost techniques and also recognized from the real-time images. Objects are detected using AdaBoost classifier. SIFT features are extracted from the objects found in the image and classified using Support Vector Machine, and the position of an objects are estimated. We proposed IOLE algorithm to estimate the location of object in an image

scholarly journals A survey on computer vision technology in Camera Based ETA devices

2015 ◽  
Vol 1 (3) ◽  
pp. 115
Author(s):  
Amir Ramezani Dooraki
Keyword(s):  
Computer Vision ◽  
Object Recognition ◽  
Computer Science ◽  
Stereo Vision ◽  
Visually Impaired ◽  
High Potential ◽  
Methods And Techniques ◽  
Computer Vision Technology ◽  
Visually Impaired Persons ◽  
Vision Technique

Electronic Travel Aid systems are expected to make impaired persons able to perform their everyday tasks such as finding an object and avoiding obstacles easier. Among ETA devices, Camera Based ETA devices are the new one and with a high potential for helping Visually Impaired Persons. With recent advances in computer science and specially computer vision, Camera Based ETA devices used several computer vision algorithms and techniques such as object recognition and stereo vision in order to help VIP to perform tasks such as reading banknotes, recognizing people and avoiding obstacles. This paper analyses and appraises a number of literatures in this area with focus on stereo vision technique. Finally, after discussing about the methods and techniques used in different literatures, it is concluded that the stereo vision is the best technique for helping VIP in their everyday navigation.

Real-Time Linux Control of a Haptic Interface for Visually Impaired Persons

2000 ◽  
Vol 33 (27) ◽  
pp. 669-674 ◽  
Author(s):  
A. Macchelli ◽  
C. Melchiorri ◽  
D. Arduini
Keyword(s):  
Real Time ◽  
Visually Impaired ◽  
Haptic Interface ◽  
Visually Impaired Persons

scholarly journals Real Time Object Recognition and Classification using Deep Learning

2019 ◽  
pp. 355-359
Author(s):  
Kiruthiga N ◽  
Divya E ◽  
Haripriya R ◽  
Haripriya V.
Keyword(s):  
Deep Learning ◽  
Object Recognition ◽  
Object Detection ◽  
Real Time ◽  
Visually Impaired ◽  
Detection Algorithm ◽  
Indoor Environments ◽  
Wide Range ◽  
Impaired Person ◽  
First Time

Navigation in indoor environments is highly challenging for visually impaired person, particularly in spaces visited for the first time. Various solutions have been proposed to deal with this challenge. In this project consider as the real time object Recognition and classification using deep learning algorithms. Object detection mainly deals with identification of real time objects such as people, animals, and objects. Object detection algorithm uses a wide range of image processing applications for extracting the object's desired portion. This enables one to identify the objects and calculate the accuracy of the object and deliver through voice. Using this information, the system determines the user's trajectory and can locate possible obstacles in that route.

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