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Collaborative Projects


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Multi-resolution signal processing in computer vision

Shearlets are a multi-resolution analysis framework with many suitable properties for it to be applied to the analysis of images and videos. Among these, we mention its ability in characterizing anisotropic structures, and in enhancing signal singularities. For these reasons, we have adopted it in the detection and descriptions of keypoints in images and image sequences. Its robustness to noise (including motion blur and compression artifacts), makes it suitable to address different applications in the signal processing domain.


Collaboration with


Reference papers


Marine robotics

Unmanned Surface Vehicles (USVs) are autonomous boats that have different applications, ranging from patrolling and monitoring of the waterways for security reasons, to scientific applications such as sampling the water for pollution or biological investigations. One of the major research themes to be tackled, for the widespread adoption of USVs, is the development of reliable obstacle detection and avoidance systems. In this research we investigate data fusion of LIDAR sensors and video-cameras, for efficient detection of potential obstacles, in port areas and open sea.


Collaboration with


Reference papers

M Sorial, I Mouawad, E Simetti, F Odone, G Casalino. Towards a Real Time Obstacle Detection System for Unmanned Surface Vehicles OCEANS 2019 ISME


Robot Vision

Visual perception is an important cue for understanding and interacting with the surrounding environment, and robotics is one of the main application fields where this ability can be appreciated. Here we mention two of the most relevant collaborations we have in this field.

  • Indoor exploration (with IIT): we specialize to the robotics scenario object detection and object recognition tasks. In this context we also participate in the acquisition of the iCubWorld dataset, a growing dataset built through human-robot interaction
    G Pasquale, C Ciliberto, F Odone, L Rosasco, L Natale Are we done with object recognition? the iCub robot’s perspective Robotics and Autonomous Systems 112, 260-281, 2019
  • 6D object pose estimation (with Marquette): we explore the use of deep architectures in robotic scenarios to solve the 6D pose estimation task; we also participate to the design of a robotic platform for semi-automatic acquisitions of annotated data, to ease benchmarking in this specific application domain.


Collaboration with

  • Marquette University

  • IIT