# Polyhedral Object Recognition by Indexing

arXiv: https://arxiv.org/abs/2311.12641 · HTML: https://mlsanity.com/paper/2311.12641/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 39 references that are in the map.
- First posted on arXiv 21 Nov 2023.

## Built on by (most cited first, 1 of 1)

- [A Unified Framework for Integer Programming Formulation of Graph Matching Problems](https://mlsanity.com/paper/2406.07666/) (2024)

## Abstract (arXiv)

In computer vision, the indexing problem is the problem of recognizing a few objects in a large database of objects while avoiding the help of the classical image-feature-to-object-feature matching paradigm. In this paper we address the problem of recognizing 3-D polyhedral objects from 2-D images by indexing. Both the objects to be recognized and the images are represented by weighted graphs. The indexing problem is therefore the problem of determining whether a graph extracted from the image is present or absent in a database of model graphs. We introduce a novel method for performing this graph indexing process which is based both on polynomial characterization of binary and weighted graphs and on hashing. We describe in detail this polynomial characterization and then we show how it can be used in the context of polyhedral object recognition. Next we describe a practical recognition-by-indexing system that includes the organization of the database, the representation of polyhedral objects in terms of 2-D characteristic views, the representation of this views in terms of weighted graphs, and the associated image processing. Finally, some experimental results allow the evaluation of the system performance.