45,145 research outputs found
An AI-based object detection approach for robotic competitions
Artificial Intelligence has been introduced in many
applications, namely in artificial vision-based systems with object
detection tasks. This paper presents an object localization system
with a motivation to use it in autonomous mobile robots at
robotics competitions. The system aims to allow robots to accomplish
their tasks more efficiently. Object detection is performed
using a camera and artificial intelligence based on the YOLOv4
Tiny detection model. An algorithm was developed that uses the
data from the system to estimate the parameters of location,
distance, and orientation based on the pinhole camera model and
trigonometric modelling. It can be used in smart identification
procedures of objects. Practical tests and results are presented,
constantly locating the objects and with errors between 0.16 and
3.8 cm, concluding that the object localization system is adequate
for autonomous mobile robots.The authors are grateful to the Foundation for Science
and Technology (FCT, Portugal) for financial support
through national funds FCT/MCTES (PIDDAC) to CeDRI
(UIDB/05757/2020 and UIDP/05757/2020). The project that
gave rise to these results received the support of a fellowship
from ”la Caixa” Foundation (ID 100010434). The fellowship
code is LCF/BQ/DI20/11780028. João Braun is a PhD Student
at the Faculty of Engineering, University of Porto (FEUP)
supervised by Prof. Paulo Costa.info:eu-repo/semantics/publishedVersio
The Evolution of First Person Vision Methods: A Survey
The emergence of new wearable technologies such as action cameras and
smart-glasses has increased the interest of computer vision scientists in the
First Person perspective. Nowadays, this field is attracting attention and
investments of companies aiming to develop commercial devices with First Person
Vision recording capabilities. Due to this interest, an increasing demand of
methods to process these videos, possibly in real-time, is expected. Current
approaches present a particular combinations of different image features and
quantitative methods to accomplish specific objectives like object detection,
activity recognition, user machine interaction and so on. This paper summarizes
the evolution of the state of the art in First Person Vision video analysis
between 1997 and 2014, highlighting, among others, most commonly used features,
methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart
Glasses, Computer Vision, Video Analytics, Human-machine Interactio
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