Irving Hofman

About

Irving Hofman’s research centers on machine vision and three-dimensional scene analysis, with a focus on developing complete, end-to-end systems for object recognition and spatial understanding. His most cited work, "Object recognition via attributed graph matching" (2000), describes a comprehensive machine vision system implemented at Monash University that integrates data acquisition, segmentation, modeling, and matching to produce a near-complete scene description—including object identity, location, and pose. This contribution demonstrates his ability to bridge theoretical graph-based methods with practical, real-world applications. In earlier work, "Three-dimensional scene analysis using multiple range finders" (1997), Hofman tackled the challenges of data capture, coordinate transformations, and initial segmentation for 3D environments, laying groundwork for multi-sensor fusion. Though his citation counts are modest (4 and 2 respectively), his contributions reflect a pioneering effort in automating complex visual tasks at a time when such systems were nascent. Hofman’s work remains relevant for researchers exploring integrated vision pipelines and graph-based matching in robotics and autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Object recognition via attributed graph matching

   4 citations · 2000
2. 2
   Three-dimensional scene analysis using multiple range finders — Data capture, coordinate transformations and initial segmentation

   2 citations · 1997

Key Collaborators

Contact & Links