Visual Information Processing and Management

Dr. Simone Bianco, Dr. Gianluigi Ciocca, Dr. Paolo Napoletano, Prof. Raimondo Schettini

University of Milano-Bicocca, Milano, Italy

The goals of this course are to understand the strengths and weaknesses of the state-of-the-art approaches in the field of visual information processing, recognition and retrieval. The course will consist of lectures given by the instructors and case studies presentations.


Final exam may be done in teams of two or three, depending on the total number of students enrolled in the course. Each team will have to write a draft paper (4–8 pages) on the agreed topic.

Detailed program


  • Understanding Image quality dimensions
  • Understanding image classification problems
  • Understanding image retrieval problems

Acquire and reproduce images

  • Digital camera acquisition pipeline
  • Color description and management

Image to image transformation

  • Image enhancement and restoration
  • Non-photorealistic image rendering

Convolutional neural networks (CNN)

  • CNN architectures
  • Training CNNs for regression
  • Training CNNs for image classification
  • Fine-tuning of pre-trained nets (transfer learning) for image tagging

Image features extraction

  • Hand-crafted (Color, texture and shape description)
  • Salient point detection and description
  • bag-of-words representations
  • Learned features

Image classification

  • Understanding Image classification
  • Early and late fusion strategies
  • Performance assessment

Image retrieval

  • Instance based image retrieval
  • Content based image similarity retrieval
  • Performance assessment

Case studies and demos


Mon 2/7: 9:30-12:30, 14:30-17:30
Tue 3/7: 9:30-12:30, 14:30-17:30
Wed 4/7: 9:30-12:30, 14:30-17:30
Thu 5/7: 9:30-12:30, 14:30-17:30
Fri 6/7: 9:30-12:30, 14:30-17:30

meeting room of the III floor – U14