[HTML][HTML] Human activity recognition in artificial intelligence framework: a narrative review
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …
acquisition devices such as smartphones, video cameras, and its ability to capture human …
Recent methods and databases in vision-based hand gesture recognition: A review
PK Pisharady, M Saerbeck - Computer Vision and Image Understanding, 2015 - Elsevier
Successful efforts in hand gesture recognition research within the last two decades paved
the path for natural human–computer interaction systems. Unresolved challenges such as …
the path for natural human–computer interaction systems. Unresolved challenges such as …
MMTM: Multimodal transfer module for CNN fusion
In late fusion, each modality is processed in a separate unimodal Convolutional Neural
Network (CNN) stream and the scores of each modality are fused at the end. Due to its …
Network (CNN) stream and the scores of each modality are fused at the end. Due to its …
A low power, fully event-based gesture recognition system
We present the first gesture recognition system implemented end-to-end on event-based
hardware, using a TrueNorth neurosynaptic processor to recognize hand gestures in real …
hardware, using a TrueNorth neurosynaptic processor to recognize hand gestures in real …
First-person hand action benchmark with rgb-d videos and 3d hand pose annotations
G Garcia-Hernando, S Yuan… - Proceedings of the …, 2018 - openaccess.thecvf.com
In this work we study the use of 3D hand poses to recognize first-person dynamic hand
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …
Online detection and classification of dynamic hand gestures with recurrent 3d convolutional neural network
Automatic detection and classification of dynamic hand gestures in real-world systems
intended for human computer interaction is challenging as: 1) there is a large diversity in …
intended for human computer interaction is challenging as: 1) there is a large diversity in …
Real-time hand gesture detection and classification using convolutional neural networks
Real-time recognition of dynamic hand gestures from video streams is a challenging task
since (i) there is no indication when a gesture starts and ends in the video,(ii) performed …
since (i) there is no indication when a gesture starts and ends in the video,(ii) performed …
EgoGesture: A new dataset and benchmark for egocentric hand gesture recognition
Gesture is a natural interface in human-computer interaction, especially interacting with
wearable devices, such as VR/AR helmet and glasses. However, in the gesture recognition …
wearable devices, such as VR/AR helmet and glasses. However, in the gesture recognition …
Hand gesture recognition with 3D convolutional neural networks
Touchless hand gesture recognition systems are becoming important in automotive user
interfaces as they improve safety and comfort. Various computer vision algorithms have …
interfaces as they improve safety and comfort. Various computer vision algorithms have …
Drive&act: A multi-modal dataset for fine-grained driver behavior recognition in autonomous vehicles
We introduce the novel domain-specific Drive&Act benchmark for fine-grained
categorization of driver behavior. Our dataset features twelve hours and over 9.6 million …
categorization of driver behavior. Our dataset features twelve hours and over 9.6 million …