Selected publications

Article

Wang, Lin, Gjoreski, Hristijan, Ciliberto, Mathias, Lago, Paula, Murao, Kazuya, Okita, Tsuyoshi and Roggen, Daniel (2021) Three-year review of the 2018–2020 SHL challenge on transportation and locomotion mode recognition from mobile sensors. Frontiers in Computer Science, 3. pp. 1-24. ISSN 2624-9898

Wang, Lin, Gjoreski, Hristijan, Ciliberto, Mathias, Mekki, Sami, Valentin, Stefan and Roggen, Daniel (2019) Enabling reproducible research in sensor-based transportation mode recognition with the Sussex-Huawei dataset. IEEE Access, 7. pp. 10870-10891. ISSN 2169-3536

Gjoreski, Hristijan, Ciliberto, Mathias, Wang, Li, Ordonez Morales, Francisco Javier, Mekki, Sami, Valentin, Stefan and Roggen, Daniel (2018) The University of Sussex-Huawei locomotion and transportation dataset for multimodal analytics with mobile devices. IEEE Access, 6. pp. 42592-42604. ISSN 2169-3536

Book Section

Templeman, Charles, Ordonez Morales, Francisco Javier, Ciliberto, Mathias, Symes, Andrew and Roggen, Daniel (2020) Lessons from hands-free data entry in flexible cystoscopy with Glass for future smart assistance. In: Chen, Feng, García-Betances, Rebaca I, Chen, Liming, Cabrera-Umpiérrez, María Fernanda and Nugent, Chris (eds.) Smart assisted living: toward an open smart-home infrastructure. Computer Communications and Networks . Springer International Publishing, Switzerland, pp. 63-87. ISBN 9783030255893

Conference or Workshop Item

Gjoreski, Hristijan, Ciliberto, Mathias, Ordoñez Morales, Francisco Javier, Roggen, Daniel, Mekki, Sami and Valentin, Stefan (2017) A versatile annotated dataset for multimodal locomotion analytics with mobile devices. In: The 15th ACM Conference on Embedded Networked Sensor Systems (SenSys 2017), Sunday 5th - Wednesday 8th November 2017, Delft, The Netherlands.

Ciliberto, Mathias, Ordonez Morales, Francisco Javier and Roggen, Daniel (2016) Exploring human activity annotation using a privacy preserving 3D Model. In: HASCA Workshop at Ubicomp, 12-16 September 2016, Heidelberg, Germany.

Conference Proceedings

Ciliberto, Mathias and Roggen, Daniel (2019) WLCSSCuda: a CUDA accelerated template matching method for gesture recognition. ISWC 2019: International Symposium on Wearable Computers, London, 9-13 September 2019. Published in: Dunne, Lucy, Cakmakci, Ozan, Ward, Jamie, Unset, Unset, Unset, Unset and Unset, (eds.) Proceedings of the 2019 International Symposium on Wearable Computers. 32-34. Association for Computing Machinery ISBN 9781450368704

Richoz, Sebastian, Ciliberto, Mathias, Wang, Lin, Birch, Philip, Gjoreski, Hristijan, Perez-Uribe, Andres and Roggen, Daniel (2019) Human and machine recognition of transportation modes from body-worn camera images. International Conference on Activity and Behavior Computing, Spokane, Eastern Washington University, USA, May. 30 - Jun. 2, 2019. Published in: Inoue, Sozo and Rahman Ahad, Atiqur, (eds.) International Conference on Activity and Behavior Computing. 1 67-72. Institute of Electrical and Electronics Engineers

Ciliberto, Mathias, Ponce Cuspinera, Luis and Roggen, Daniel (2019) WLCSSLearn: learning algorithm for template matching-based gesture recognition systems. Internatoinal Conference on Activity and Behavior Computing, Spokane, Eastern Washington University, USA, May. 30 - Jun. 2, 2019. Published in: Inoue, Sozo and Rahman Ahad, Atiqur, (eds.) ICIEV-&-ICIVPR 2019. 1 91-96. Institute of Electrical and Electronics Engineers ISBN 9781728107868

Wang, Lin, Gjoreski, Hristijan, Ciliberto, Mathias, Mekki, Sami, Stefan, Valentin and Roggen, Daniel (2018) Benchmarking the SHL Recognition Challenge with classical and deep-learning pipelines. HASCA Workshop at Ubicomp 2018, Singapore, 8-12 October 2018. Published in: Murao, Kazuya, Enokibori, Yu, Gjoreski, Hristijan, Lago, Paula, Okita, Tsuyoshi, Siirtola, Pekka, Hiroi, Kei and Scholl, Philipp, (eds.) Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers. 1626-1635. Association for Computing Machinery ISBN 9781450359665

Ciliberto, Mathias, Roggen, Daniel, Wang, Lin and Zillmer, Ruediger (2018) A case study for human gesture recognition from poorly annotated data. UbiComp '18, Singapore, 9th - 11th October, 2018. Published in: UbiComp '18 Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers. 1434-1443. Association for Computing Machinery, New York. ISBN 9781450359665

Roggen, Daniel, Pouryazdan, Arash and Ciliberto, Mathias (2018) BlueSense: designing an extensible platform for wearable motion sensing, sensor research and IoT applications. EWSN International Conference on Embedded Wireless Systems and Networks, Madrid, Spain, February 14-16, 2018. Published in: Giustiniano, Domenico and Koutsonikolas, Dimitrios, (eds.) EWSN ’18 Proceedings of the 2018 International Conference on Embedded Wireless Systems and Networks. 177-178. ACM ISBN 9780994988621

Ciliberto, Mathias, Ponce Cuspinera, Luis and Roggen, Daniel (2018) Demo: Complex human gestures encoding from wearable inertial sensors for activity recognition. International Conference on Embedded Wireless Systems and Networks, Madrid, Spain, February 14-16, 2018. Published in: Giustiniano, Domenico and Koutsonikolas, Dimitrios, (eds.) EWSN ’18 Proceedings of the 2018 International Conference on Embedded Wireless Systems and Network. 193-194. Association for Computing Machinery ISBN 9780994988621

Ciliberto, Mathias, Ordonez Morales, Francisco Javier, Gjoreski, Hristijan, Roggen, Daniel, Mekki, Sami and Valentin, Stefan (2017) High reliability Android application for multidevice multimodal mobile data acquisition and annotation. 15th ACM Conference on Embedded Networked Sensor Systems, Delft, Netherlands, 5-8 November. Published in: Markham, Andrew and Zuniga, Marco, (eds.) SenSys '17 Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. ACM ISBN 9781450354592

Thesis

Ciliberto, Mathias (2021) Movement recognition from wearable sensors data: power-aware evolutionary training for template matching and data annotation recovery methods. Doctoral thesis (PhD), University of Sussex.