Results 31 to 40 of about 15,698 (301)
Transformation invariance in hand shape recognition [PDF]
, 2006 In hand shape recognition, transformation invariance is key for successful recognition. We propose a system that is invariant to small scale, translation and shape variations.
T. Coogan +3 more
core +1 more source
Lixdh12/Hand-Gesture-Recognition-Using-Background-Elllimination-and-Convolution-Neural-Network:
, 2021 Hand Gesture Recognition using Convolution Neural Network built using Tensorflow, OpenCV and ...
Sparsha Saha, mohammed-Emad
core +1 more source
Hand Motion and Posture Recognition in a Network of Calibrated Cameras
Advances in Multimedia, 2017 This paper presents a vision-based approach for hand gesture recognition which combines both trajectory and hand posture recognition. The hand area is segmented by fixed-range CbCr from cluttered and moving backgrounds and tracked by Kalman Filter.
Jingya Wang, Shahram Payandeh
doaj +1 more source
Hand gesture recognition with depth data [PDF]
Proceedings of the 4th ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream, 2013 Depth data acquired by current low-cost real-time depth cameras provide a very informative description of the hand pose, that can be effectively exploited for gesture recognition purposes. This paper introduces a novel hand gesture recognition scheme based on depth data.
DOMINIO, FABIO +4 more
openaire +2 more sources
REST Journal on Data Analytics and Artificial IntelligenceThe "Real-Time Hand Gesture Recognition System" aims to enhance human-computer interaction using computer vision and machine learning techniques. Using the webcam for real-time video capture, the system uses OpenCV to process each frame in real-time. Thus, it recognizes hand gestures using models such as Cvzone's, Hand Detector or Mediapipe.
null Prof. Elia R. Chandane +4 more
+4 more sources
Skeleton-Based Dynamic Hand Gesture Recognition Using an Enhanced Network with One-Shot Learning
Applied Sciences, 2020 Dynamic hand gesture recognition based on one-shot learning requires full assimilation of the motion features from a few annotated data. However, how to effectively extract the spatio-temporal features of the hand gestures remains a challenging issue ...
Chunyong Ma +4 more
doaj +1 more source
Two-Dimensional Parallel Spatio-Temporal Pyramid Pooling for Hand Gesture Recognition
IEEE Access, 2023 Hand Gesture Recognition (HGR) plays a crucial role in user-friendly interactions between humans and computers. In recent years, using the Convolutional Neural Network (CNN) has improved the accuracy of image processing problems.
Farzaneh Jafari, Anup Basu
doaj +1 more source
HAGR-D: A Novel Approach for Gesture Recognition with Depth Maps
Sensors, 2015 The hand is an important part of the body used to express information through gestures, and its movements can be used in dynamic gesture recognition systems based on computer vision with practical applications, such as medical, games and sign language ...
Diego G. Santos +2 more
doaj +1 more source
Ultra-Low Power Hand Gesture Sensor Using Electrostatic Induction
Sensors, 2021 This paper presents an ultra-low power hand gesture sensor using electrostatic induction for mobile devices. Two electrodes, which consist of electret foils stacked on metal sheets, are used to recognize two gestures such as hand movements from left to ...
Hiroshi Fuketa
doaj +1 more source
Sparse representations for hand gesture recognition [PDF]
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 Dynamic recognition of gestures from video sequences is a challenging task due to the high variability in the characteristics of each gesture with respect to different individuals. In this work, we propose a novel representation of gestures as linear combinations of the elements of an overcomplete dictionary, based on the emerging theory of sparse ...
Stergios Poularakis +3 more
openaire +1 more source