Massimo Piccardi
University of Technology Sydney, University of Ferrara, University of Bologna
Papers
8
Total Citations
127
H-Index
3
About
Massimo Piccardi is a leading researcher in computer vision and human-robot interaction, whose work bridges the gap between machine perception and real-world applications. His most cited paper, "From the Lab to the Real World: Affect Recognition Using Multiple Cues and Modalities" (2008, 89 citations), tackles the challenge of enabling machines to interpret human emotions through multimodal sensing—a foundational contribution to affective computing. Piccardi’s early work on industrial robotics, such as "Focus based Feature Extraction for Pallets Recognition" (2000, 20 citations), demonstrates his long-standing commitment to practical automation, while his development of the GIOTTO parallel computing system (1997) highlights his expertise in high-performance vision architectures. More recently, he has advanced fine-grained activity recognition from depth videos and still images, with papers like "Local depth patterns for fine-grained activity recognition in depth videos" (2016) and "Learning Spatial Affordances From 3D Point Clouds for Mapping Unseen Human Actions in Indoor Environments" (2023). These contributions are critical for applications ranging from assistive robotics to video surveillance. With over 120 citations across his most-cited works, Piccardi’s research continues to shape how machines perceive and interact with complex, human-centric environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Focus based Feature Extraction for Pallets Recognition20 citations · 2000
- 3The GIOTTO System: a Parallel Computer for Image Processing5 citations · 1997
- 4
- 5
- 6Action recognition in still images by latent superpixel classification3 citations · 2015
- 7Static action recognition by efficient greedy inference2 citations · 2016
- 8A parallel vision subsystem for robotic inspection and manipulation2 citations · 2002