Multi‐Segment Foot for Human Modelling and Simulation. (25th December 2019)

• Record Type: Journal Article
• Authors: Park, Hwangpil; Yu, Ri; Lee, Jehee
• Is Part Of: Computer graphics forum. Volume 39:Number 1(2020)
• Page Start: 637
• Page End: 649
• Publication Date: 2019-12-25
• Subjects: physically based animation -- human simulation -- motion control -- Computing methodologies → Physical simulation; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.13896
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract: Realistic modelling of a human‐like character is one of the main topics in computer graphics to simulate human motion physically and also look realistically. Of the body parts, a human foot interacts with the ground, and plays an essential role in weight transmission, balancing posture and assisting ambulation. However, in the previous researches, the foot model was often simplified into one or two rigid bodies connected by a revolute joint. We propose a new foot model consisting of multiple segments to reproduce human foot shape and its functionality accurately. Based on the new model, we develop a foot pose controller that can reproduce foot postures that are generally not obtained in motion capture data. We demonstrate the validity of our foot model and the effectiveness of our foot controller with a variety of foot motions in a physics‐based simulation. Abstract : Realistic modelling of a human‐like character is one of the main topics in computer graphics to simulate human motion physically and also look realistically. Of the body parts, a human foot interacts with the ground, and plays an essential role in weight transmission, balancing posture and assisting ambulation. However, in the previous researches, the foot model was often simplified into one or two rigid bodies connected by a revolute joint. We propose a new foot model consisting of multiple segments to reproduce human foot shape and its functionality accurately. Based on the new model, we develop a foot pose controller that can reproduce foot postures that are generally not obtained in motion capture data. We demonstrate the validity of our foot model and the effectiveness of our foot controller with a variety of foot motions in a physics‐based simulation.