A REVIEW OF VISION BASED HAND GESTURES RECOGNITION

By G. Murthy, R. S. Jadon. 2009

390 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/836dd170045a02a1d20a22c13ed89ed02b203e70

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. J. Urgen Schmidhuber
2. Yoshua Bengio
3. Sergey Levine
4. Dan Claudiu Ciresan
5. Xiaogang Wang
6. Liang-Chieh Chen
7. Trevor Darrell
8. Junsong Yuan

Citations in the corpus

• A review of verbal and non-verbal human-robot interactive communication (2014, background): “Apart from a wealth of existing research on automated production and recognition of sign language for the deaf (ASL) [200] [201] [202], systems directly adaptable to robots also exist [203].”
• A review of hand gesture and sign language recognition techniques (2017, background): “Most researches done might be suitable in a controlled lab setting but does not generalize to arbitrary setting [37].”
• Robust Part-Based Hand Gesture Recognition Using Kinect Sensor (2013, background): “Despite lots of previous work, traditional vision-based hand gesture recognition methods [5]–[7] are still far from satisfactory for real-life applications.”
• Gesture Recognition: A Survey (2016, background): “2) Gestures using hands and arms: recognition of gestures involving movements of hands and arm [4].”
• Max-pooling convolutional neural networks for vision-based hand gesture recognition (2011, background): “Recently, different research efforts on 2D appearance model-based methods for gesture recognition have emerged [9], [10], [11], [12], [13], [14], [15], amongst which supervised and unsupervised learning techniques such as Neural Networks (NNs), Support Vector Machine (SVMs) and NearestNeighbor [16],”
• Hand Gesture Recognition Based on Computer Vision: A Review of Techniques (2020, background): “…involves several challenges, including lighting variation, background issues, the e ect of occlusions, complex background, processing time traded against resolution and frame rate and foreground or background objects presenting the same skin color tone or otherwise appearing as hands [17,21].”
• Vision-based human activity recognition: a survey (2020, background): “Ontheother hand, reviews of vision-based hand gesture recognition methods were presented in [33, 34, 45, 64, 119, 145, 153, 227].”
• Fusion of Inertial and Depth Sensor Data for Robust Hand Gesture Recognition (2014, unknown): “2306094 have previously appeared in [1]–[3].”