School of
Information Technology and Electrical Engineering

Embedded Computer Vision for Safety and Security: an FPGA-based Approach for Detection and Classification

Dr. Samuele Martelli, Post-Doc at the Pattern Analysis and Computer Vision department (PAVIS), Italian Institute of TechnologyThu, 12/12/2013 - 11:00
Prof. Brian Lovell

Automatic classifying different categories of objects in images and videos is one of the main goals in Computer Vision. Among them, classifying pedestrians has attracted considerable attention as a key component in different application domains such as video surveillance, navigation systems and robotic control.

Despite continuous efforts over recent years to improve accuracy and processing performance, they are not ready for real-world applications yet. Additionally, although hardware solutions have recently demonstrated their reliability to solve some problems in Computer Vision, few object detection systems are thought to be realized on embedded devices.

The recent development of new System on Chips (SoC), where processors, programmable logic and key peripherals are in a single device, brings new challenges by the possibility of non-serialized hardware/software partitioning. Moreover, it paves the way towards smarter and ubiquitous  embedded vision systems capable of automatically detecting objects of interest directly in the field.

In this seminar, after a brief introduction of the PAVIS department, I  will present our ongoing research towards developing robust pedestrian detection systems targeting surveillance and automotive applications. In particular, I will describe our FPGA-based pedestrian detection architecture using covariance matrices as object descriptor, and I will discuss recent advances in object detection using multi-cue features extracted from intensity, depth and motion.


Samuele Martelli received the MSc (Laurea degree) in Telecommunication Engineering at the University of Siena in 2007. He received the Ph.D. in Computer Science from the University of Verona (Italy) in 2012 and now he is post-doc in the group of Pattern Analysis and Computer Vision (PAVIS) at the Italian Institute of Technology (IIT) in Genoa, Italy.

His main research field is embedded computer vision, in particular the design and development of computer vision algorithms on Field Programmable Gate Arrays (FPGA).  In the last few years he also explored the possibility to employ multiple imaging technologies such as optical images, 3D information from stereo cameras and thermal images to boost current object detection algorithms. He is co-author of research articles published on international conference proceedings. He was also involved in several projects in collaboration with companies and international research centers including the School of Surveying and Spatial Information Systems at the University of New South Wales (UNSW) in Sydney (Australia), Embedded Vision Systems s.r.l.  and Azimut-Benetti Yacht Group.

He is a Member of the IEEE, SPS and CVF (Computer Vision Foundation ).

Seminar Type: 

ITEE Research Seminar