Awards

Most Influential Paper over the Decade Award

This award is given to the authors of papers that were presented at the conference held ten years before (this time IAPR MVA 2002) and have been recognized as having the most significant influence on machine vision technologies over the subsequent decade.

Mickael Pic, Luc Berthouze and Takio Kurita

for the paper entitled 'Adaptive Background Estimation' in IAPR Workshop on Machine Vision Applications 2002

Raphael Labayrade and Didier Aubert

for the paper entitled 'Robust and Fast Stereovision Based Road Obstacles Detection for Driving Safety Assistance' in IAPR Workshop on Machine Vision Applications 2002

Shorin Kyo

for the paper entitled 'A 51.2 GOPS Programmable Video Recognition Processor for Vision-Based Intelligent Cruise Control Applications' in IAPR Workshop on Machine Vision Applications 2002

Best Paper Award

This award is given to the authors of an paper that is most excellent from the viewpoint of machine vision applications.

Simon Stent, Riccardo Gherardi, Björn Stenger, Kenichi Soga, and Roberto Cipolla

for the paper entitled 'An Image-Based System for Change Detection on Tunnel Linings'

Best Practical Paper Award

This award is given to the authors of the most excellent paper whose technology is already or expected to be used shortly in practice.

Frank Nielsen

for the paper entitled 'Perspective Click-and-drag Area Selections in Pictures'

Best Poster Award

This award is given to the authors of the best poster paper selected by votes of all participants based on both technical merits and presentation.

Victor Borjas, Jordi Vitrià, and Petia Radeva

for the paper entitled 'Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments'

Sara Atito Aly, Ahmed Mamdouh, and Moatz Abdelwahab

for the paper entitled 'Vehicles Detection and Tracking in Videos for Very Crowded Scenes'

Yasunori Ishii, Toshiya Arai, Yasuhiro Mukaigawa, Junichi Tagawa, and Yasushi Yagi

for the paper entitled 'Scattering Tomography by Monte Carlo Voting'