Journal ArticleDOI
Hand posture and gesture recognition techniques for virtual reality applications: a survey
TLDR
A survey on hand posture and gesture is clarified with a detailed comparative analysis of hidden Markov model approach with other classifier techniques, and difficulties and future investigation bearing are also examined.Abstract:
Motion recognition is a topic in software engineering and dialect innovation with a goal of interpreting human signals through mathematical algorithm. Hand gesture is a strategy for nonverbal communication for individuals as it expresses more liberally than body parts. Hand gesture acknowledgment has more prominent significance in planning a proficient human computer interaction framework, utilizing signals as a characteristic interface favorable to circumstance of movements. Regardless, the distinguishing proof and acknowledgment of posture, gait, proxemics and human behaviors is furthermore the subject of motion to appreciate human nonverbal communication, thus building a richer bridge between machines and humans than primitive text user interfaces or even graphical user interfaces, which still limits the majority of input to electronics gadget. In this paper, a study on various motion recognition methodologies is given specific accentuation on available motions. A survey on hand posture and gesture is clarified with a detailed comparative analysis of hidden Markov model approach with other classifier techniques. Difficulties and future investigation bearing are also examined.read more
Citations
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Journal ArticleDOI
Vision-based human activity recognition: a survey
TL;DR: Most computer vision applications such as human computer interaction, virtual reality, security, video surveillance and home monitoring are highly correlated to HAR tasks, which establishes new trend and milestone in the development cycle of HAR systems.
Proceedings ArticleDOI
Learning Human Motion Models for Long-Term Predictions
TL;DR: In this article, a Dropout Autoencoder LSTM (DAELSTM) is proposed to synthesize natural looking motion sequences over long-time horizons without catastrophic drift or motion degradation.
Journal ArticleDOI
Review of constraints on vision-based gesture recognition for human–computer interaction
TL;DR: Major constraints on vision-based gesture recognition occurring in detection and pre-processing, representation and feature extraction, and recognition are surveyed.
Posted Content
Learning Human Motion Models for Long-term Predictions
TL;DR: The Dropout Autoencoder LSTM (DAELSTM), a new architecture for the learning of predictive spatio-temporal motion models from data alone, is capable of synthesizing natural looking motion sequences over long-time horizons without catastrophic drift or motion degradation.
Journal ArticleDOI
Extended Reality in Spatial Sciences: A Review of Research Challenges and Future Directions
Arzu Çöltekin,Ian Lochhead,Marguerite Madden,Sidonie Christophe,Alexandre Devaux,Christopher Pettit,Oliver Lock,Shashwat Shukla,Lukáš Herman,Zdeněk Stachoň,Petr Kubíček,Dajana Snopková,Sergio Bernardes,Nicholas Hedley +13 more
TL;DR: The main objective of the study is to provide an overview of broader research challenges and directions in XR, especially in spatial sciences, and to provide case studies with original results from their own studies in each section.
References
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