Topological Structure Description for Artcode Detection Using the Shape of Orientation Histogram

TL;DR

This paper introduces a novel topological feature descriptor called the shape of orientation histogram for detecting Artcodes, which are decorative, machine-readable markers that encode information through topology, enabling new AR/VR interaction possibilities.

Contribution

It proposes a new topological feature descriptor for recognizing Artcodes and demonstrates its effectiveness through dataset collection and comprehensive experiments.

Findings

The shape of orientation histogram effectively describes topological structures.

The system successfully detects Artcode proposals with promising accuracy.

The approach opens new avenues for topological object detection in AR/VR.

Abstract

The increasing ubiquity of smartphones and resurgence of VR/AR techniques, it is expected that our everyday environment may soon be decorating with objects connecting with virtual elements. Alerting to the presence of these objects is therefore the first step for motivating follow-up further inspection and triggering digital material attached to the objects. This work studies a special kind of these objects -- Artcodes -- a human-meaningful and machine-readable decorative markers that camouflage themselves with freeform appearance by encoding information into their topology. We formulate this problem of recongising the presence of Artcodes as Artcode proposal detection, a distinct computer vision task that classifies topologically similar but geometrically and semantically different objects as a same class. To deal with this problem, we propose a new feature descriptor, called the shape of orientation histogram, to describe the generic topological structure of an Artcode. We collect datasets and conduct comprehensive experiments to evaluate the performance of the Artcode detection proposer built upon this new feature vector. Our experimental results show the feasibility of the proposed feature vector for representing topological structures and the effectiveness of the system for detecting Artcode proposals. Although this work is an initial attempt to develop a feature-based system for detecting topological objects like Artcodes, it would open up new interaction opportunities and spark potential applications of topological object detection.