首页|Reports Outline Artificial Intelligence Study Findings from University of Almeri a (Point Cloud Deep Learning Solution for Hand Gesture Recognition)

Reports Outline Artificial Intelligence Study Findings from University of Almeri a (Point Cloud Deep Learning Solution for Hand Gesture Recognition)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning - Artificial Intelligence are discussed in a new report. According to news repor ting originating from Almeria, Spain, by NewsRx correspondents, research stated, "In the last couple of years, there has been an increasing need for Human-Compu ter Interaction (HCI) systems that do not require touching the devices to contro l them, such as ATMs, self service kiosks in airports, terminals in public offic es, among others. The use of hand gestures offers a natural alternative to achie ve control without touching the devices." Funders for this research include European Union (EU), Spanish Ministry of Econo my and Competitiveness (MINECO) under AEI Project. Our news editors obtained a quote from the research from the University of Almer ia, "This paper presents a solution that allows the recognition of hand gestures by analyzing three-dimensional landmarks using deep learning. These landmarks a re extracted by using a model created with machine learning techniques from a si ngle standard RGB camera in order to define the skeleton of the hand with 21 lan dmarks distributed as follows: one on the wrist and four on each finger. This st udy proposes a deep neural network that was trained with 9 gestures receiving as input the 21 points of the hand. One of the main contributions, that considerab ly improves the performance, is a first layer of normalization and transformatio n of the landmarks."

AlmeriaSpainEuropeArtificial Intel ligenceEmerging TechnologiesGesture RecognitionMachine LearningUniversit y of Almeria

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Apr.3)