KIHT: Kaligo-based Intelligent Handwriting Teacher

KIHT project overview

KIHT project overview

The KIHT project has the objective of creating an intelligent learning tool known as the "DigiPen," which is an electronic pen designed for digitized handwriting. STABILO, in collaboration with the German KIT institute, is responsible for developing the hardware of the electronic DigiPen. The KIT institute is focused on integrating artificial intelligence algorithms into the device. The IRISA IntuiDoc team is in charge of designing and developing the deep learning AI system that can reconstruct online handwriting patterns from the data captured by the DigiPen's kinematic sensors, including accelerometers, gyroscopes, magnetometers, and force sensors.


My contribution as an IRISA member

My work has focused mainly on the pre-processing chain for processing, synchronizing and labeling data (sensor and trajectory) to make it usable for deep neural network learning. We collected a significant amount of data using the latest generation Digipen. The pre-processing chain has been finalized. It is based on automatic alignment between ground truth (trajectory captured on digital tablet) and DigiPen sensor data (kinematic sensor) using the Dynamic Time Warping (DTW) algorithm. A neural network architecture based on Temporal Convolutional Networks (TCN) was designed and its hyperparameters optimized, and an evaluation based on Fréchet distance was implemented for optimum analysis of the results.

Related papers

Article in an international peer-reviewed journal (+ presentation at ICDAR 2023 – Journal Track)

[1] Online handwriting trajectory reconstruction from kinematic sensors using temporal convolutional network. Wassim Swaileh, Florent Imbert, Yann Soullard, Romain Tavenard, Eric Anquetil, IJDAR (2023)

Communication at the SIFED symposium in France without proceeding

[2] Toward Deep neural network for pen trajectory reconstruction from kinematic sensors, Florent Imbert, Eric Anquetil, Romain Tavenard, Yann Soullard, Wassim Swaileh, Symposium International Francophone sur l’Ecrit et le Document (SIFED’2022), Oct 2022, Rennes, France

Conference poster at the SIFED symposium in France without proceeding

[3] Adaptation de domaine pour la reconstruction de la trajectoire du stylo à partir de capteurs cinématiques, Florent Imbert, Eric Anquetil, Romain Tavenard, Yann Soullard, Symposium International Francophone sur l’Ecrit et le Document (SIFED’2023), Juin 2023, Paris, France

Technical Paper)

[4] Towards the on-device Handwriting Trajectory Reconstruction of the Sensor Enhanced Pen. Alexey Serdyuk, Fabian Kreß, Micha Hiegle, Tanja Harbaum, Jürgen Becker, et al.. IEEE 9th World Forum on Internet of Things, Oct 2023, Aveiro, Portugal.

[5] KIHT: Kaligo-based Intelligent Handwriting Teacher. Tanja Harbaum, Alexey Serdyuk, Fabian Kreß, Tim Hamann, Jens Barth, et al.. DATE 2024, Mar 2024, Valencia, Spain.