20.500.12556/DKUM-83622-bf7c05a8-687f-36cd-f0bc-46410cd07243 Capturing Conversational Gestures for Embodied Conversational Agents Using an Optimized Kaneda–Lucas–Tomasi Tracker and Denavit–Hartenberg-Based Kinematic Model In order to recreate viable and human-like conversational responses, the artificial entity, i.e., an embodied conversational agent, must express correlated speech (verbal) and gestures (non-verbal) responses in spoken social interaction. Most of the existing frameworks focus on intent planning and behavior planning. The realization, however, is left to a limited set of static 3D representations of conversational expressions. In addition to functional and semantic synchrony between verbal and non-verbal signals, the final believability of the displayed expression is sculpted by the physical realization of non-verbal expressions. A major challenge of most conversational systems capable of reproducing gestures is the diversity in expressiveness. In this paper, we propose a method for capturing gestures automatically from videos and transforming them into 3D representations stored as part of the conversational agent’s repository of motor skills. The main advantage of the proposed method is ensuring the naturalness of the embodied conversational agent’s gestures, which results in a higher quality of human-computer interaction. The method is based on a Kanade–Lucas–Tomasi tracker, a Savitzky–Golay filter, a Denavit–Hartenberg-based kinematic model and the EVA framework. Furthermore, we designed an objective method based on cosine similarity instead of a subjective evaluation of synthesized movement. The proposed method resulted in a 96% similarity. conversational gestures 3D gestures motor skills gesture reconstruction kinematics embodied conversational agents Kanade–Lucas–Tomasi tracker Denavit–Hartenberg kinematika človeška govorica evaluacija true true true MDPI Angleški jezik Slovenski jezik https://www.mdpi.com/1424-8220/22/21/8318 © 2022 by the authors Članek v reviji 2023-01-14 17:35:02 2023-01-20 09:00:11 2025-04-01 12:01:33 0000-00-00 00:00:00 2022 0 0 str. 8318 no. 21 Vol. 22 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2022-09-08 2022-10-27 2022-10-29 004.5 1424-8220 127923459 10.3390/s22218318 1424-8220 sensors-22-08318-v4_(2).pdf sensors-22-08318-v4_(2).pdf 1 5306D97DC6FF127430067B1CC1BE5D1F 5b018a1fd0d3aa9407b65db64a5a4ae4eb25f4184d4d0e2fb977d5daab5a9fff a08bdfb7-9429-11ed-baf4-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=165184 https://www.mdpi.com/1424-8220/22/21/8318 0 83468d15-9429-11ed-baf4-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=165183 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0