Object Detection and Tracking Using High-Speed 3D Image Sensors

3D image capture by existing LIDAR and Time-of-Flight (ToF) sensors is typically limited to relatively low frame rates due to bottleneck issues in the data readout and/or the necessity for optical scanning to cover a sufficiently large field of view. However, recent architectural innovations in ToF sensors based Single-Photon Avalanche Diodes (SPADs), such as on-chip data compression, combined with flash or blade-type illumination, are now enabling the acquisition of hundreds of frames per second. This project will develop signal processing algorithms, targeting robotics and autonomous systems, which take full advantage of the high frame rates possible with SPAD-based sensing. In particular, the emphasis will be on robust, hardware-compatible object tracking schemes, enabling low-latency actuation in a range of environmental conditions.

The project will use an existing high-speed sensor as a test platform for capturing 3D ToF data and evaluating algorithms. There will be an opportunity to contribute to the design of a next generation device, with an emphasis on identifying pathways towards “agile” 3D ToF systems, that recognise the environmental conditions, whether there is a strong ambient/scattering/fast evolving scene, and adapt the data acquisition/processing and illumination source accordingly so as to ensure optimal 3D perception.

The project benefits from a partnership with STMicroelectronics, the world’s leading manufacturer of SPAD-based ToF modules (as found in 100’s of millions of mobile phones), as well as a close association with Prof. Henderson’s Edinburgh-based CMOS Sensors & Systems Group (winners of “Best Academic Research Team” at Image Sensors Europe 2018, and one of the pioneering groups in SPADs).

The position may be closed before the deadline if a suitable candidate is found.

Further Information: 

More details on the EPSRC project that the studentship is linked to can be found at:



Closing Date: 

Monday, June 29, 2020
Object Detection and Tracking
Object Detection and Tracking

Principal Supervisor: 


Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.


Tuition fees + stipend are available for Home/EU and International students

Further information and other funding options.

Informal Enquiries: