Dr. Debaditya Acharya
Debaditya is a Lecturer in Geospatial Science at RMIT University and teaches Remote Sensing and Photogrammetry. His research interests are computer vision, machine learning, and 3D building modeling.
Previously, Debaditya worked as a CSIRO Early Research Career (CERC) Postdoctoral Fellow, CSIRO, where his work contributed to the Future Science Platforms (FSP) of Machine Learning & Artificial Intelligence (MLAI) and its applications to fisheries, especially anomaly detection using Spatio-temporal modeling, deep learning, and computer vision. Also, he worked as a postdoctoral research associate at RMIT University, Australia, working on projects related to food automation using computer vision and deep learning.
He completed his Doctor of Philosophy from the University of Melbourne, Australia, where he worked on the topic of visual sensing for indoor positioning, which aims at the development of an infrastructure-free indoor positioning technology using 3D building models. He has worked in the field of object tracking and positioning in indoor environments, using computer vision and deep learning. His research works are published in international peer-reviewed journals and international conferences.
He contributed to a project for creating a benchmark dataset for comparing the errors of 3D modeling from point cloud data, resulting in the ISPRS benchmark for indoor modeling. His past project involvement includes modeling the Royal Exhibition Building using LiDAR data, under the University of Melbourne MSE2025 project. Previously, he worked on a research engagement project with Queen Victoria Market and developed a pedestrian tracking framework using CCTV data, and liaised with LiDAR data collection for creating a 3D model.
Research: Indoor localisation, Indoor Modelling, 3D building models, Augmented Reality, Computer Vision, Machine Learning, LiDAR
Teaching: Remote Sensing and Photogrammetry
- PhD in Infrastructure Engineering from The University of Melbourne, Australia.
- MTech in Geoinformatics and Remote Sensing from IIT Bombay, India.
- BE in Mining Engineering from IIEST Shibpur, India.
- CSIRO Early Research Career Postdoctoral Fellow | Machine Learning and Artificial Intelligence (MLAI) Future Science Platform (FSP) | CSIRO
- Postdoctoral Research Associate | RMIT University
- Acharya, D.,Tennakoon, R.,Muthu, S.,Khoshelham, K.,Hoseinnezhad, R.,Bab-Hadiashar, A. (2022). Single-image localisation using 3D models: Combining hierarchical edge maps and semantic segmentation for domain adaptation In: Automation in Construction, 136, 1 - 15
- Acharya, D.,Khoshelham, K. (2021). Parking Occupancy Detection and Slot Delineation Using Deep Learning: A Tutorial In: Smart Parking in Fast-Growing Cities: Challenges and Solutions, TU Wien Academic Press, Resselgasse, Austria
- Khoshelham, K.,Tran, H.,Acharya, D.,Diaz-Vilarino, L.,Kang, Z.,Dalyot, S. (2021). Results of the ISPRS benchmark on indoor modelling In: ISPRS Open Journal of Photogrammetry and Remote Sensing, 2, 1 - 13
- Acharya, D.,Roy, S.,Khoshelham, K.,Winter, S. (2020). A recurrent deep network for estimating the pose of real indoor images from synthetic image sequences In: Sensors, 20, 1 - 20
- Zhao, H.,Acharya, D.,Tomko, M.,Khoshelham, K. (2020). Indoor lidar relocalization based on deep learning using a 3D model In: Proceedings of the 2020 Edition of the XXIVTH ISPRS Congress, Nice, Virtual, 31/08/2020-2/09/2020
- Khoshelham, K.,Tran, H.,Acharya, D.,Diaz-Vilarino, L.,Kang, Z.,Dalyot, S. (2020). The ISPRS benchmark on indoor modelling - Preliminary results In: Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Nice, Virtual, 31/08/2020-02/09/2020
- Acharya, D.,Khoshelham, K.,Winter, S. (2019). BIM-PoseNet: Indoor camera localisation using a 3D indoor model and deep learning from synthetic images In: ISPRS Journal of Photogrammetry and Remote Sensing, 150, 245 - 258
- Gu, F.,Hu, X.,Ramezani, M.,Acharya, D.,Khoshelham, K.,Valaee, S.,Shang, J. (2019). Indoor localization improved by spatial context - A survey In: ACM Computing Surveys, 52, 1 - 35
- Khoshelham, K.,Tran, H.,Acharya, D. (2019). Indoor mapping eyewear: Geometric evaluation of spatial mapping capability of hololens In: Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Enschede, The Netherlands, 10/06/2019-14/06/2019
- Acharya, D.,Roy, S.,Khoshelham, K.,Winter, S. (2019). Modelling uncertainty of single image indoor localisation using a 3D model and deep learning In: Proceedings of the ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Enschede, The Netherlands, 10/06/2019-14/06/2019