A model generation method for object recognition task by pictorial examples

D. Arita, N. Tsuruta, R. Taniguchi, M. Amamiya

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


In this paper, we describe a method to construct automatically, from a series of images of objects, a model of an object class. The model is described by a set of 2 dimensional features of segmented regions and the relations among them. To make models of objects, we introduce the concept of the segmentation tree-which represents image segmentation at various levels of abstraction-and also a model generation method based on a series of segmentation trees. Using this segmentation tree, we can cope with the problem of diversity of segmentation patterns and can easily make stable object-models.

Original languageEnglish
Article number413310
Pages (from-to)233-237
Number of pages5
JournalProceedings - International Conference on Image Processing, ICIP
Publication statusPublished - 1994
EventThe 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA
Duration: Nov 13 1994Nov 16 1994

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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