A Review of Temporal Aspects of Hand Gesture Analysis Applied to Discourse Analysis and Natural Conversation

Abstract

Lately, there has been an increasinginterest in hand gesture analysis systems. Recent works have employedpattern recognition techniques and have focused on the development of systems with more natural userinterfaces. These systems may use gestures to control interfaces or recognize sign language gestures, whichcan provide systems with multimodal interaction; or consist in multimodal tools to help psycholinguists tounderstand new aspects of discourse analysis and to automate laborious tasks.Gestures are characterizedby several aspects, mainly by movementsand sequence of postures. Since data referring to movementsorsequencescarry temporal information, this paper presents aliteraturereviewabouttemporal aspects ofhand gesture analysis, focusing on applications related to natural conversation and psycholinguisticanalysis, using Systematic Literature Review methodology. In our results, we organized works according totype of analysis, methods, highlighting the use of Machine Learning techniques, and applications

Conditional Neural Fields untuk Pengenalan Fase Gerak

“…Untuk melihat performansi dari metode yang digunakan maka penelitian ini diujikan dengan menggunakan dataset fase gerak yang berasal dari School of Art, Sciences and Humanities University of Sao Paulo [10]. Data tersebut dapat diunduh di https://archive.ics.uci.edu/ml/machine-learningdatabases/00302/gesture_phase_dataset.zip.…”