Dependable Coding of Fiducial Tags

Rice, Andrew; Cain, Christopher B.; Fawcett, John K.

doi:10.1007/11526858_20

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…The CRC-code distinguishes only between the remaining ambiguities and is variable with respect to this objective. Since it cannot be computed analytically (Rice et al, 2004), testing revealed that using the generator polynomial 0x8D (CRC-8-CCITT, (Moon, 2005)), no other than the 0-codeword must be excluded for ambiguities. We moreover assume a marker will not carry more than 60 bits and thus construct primitive RS codes over GF(16) = GF(2 4 ) = GF(q m ).…”

Section: Marker Identificationmentioning

confidence: 99%

Robust Detection and Identification of Partially Occluded Circular Markers

Köhler

Pagani

Stricker

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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In this paper we present a pipeline for the robust detection of partially occluded circular markers. Compared to square markers, occluded circular tags can be tracked in a more robust way, since the camera pose is in this case computed from the whole contour instead of only the four corners. We introduce a new ellipse detection technique based on a constrained RANSAC algorithm and pre-ellipse fit outlier removal to detect tag candidates with damaged borders. Digital codes are used to identify the actual markers afterwards, since correlation based marker identification approaches are not capable of handling occlusion. The key to error detection and correction is a suitable Reed Solomon code together with a proper code layout on the marker. We show that markers covered up to 30% can be detected, our tracker moreover has a very low risk of false positive marker detection.

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Section: Marker Identificationmentioning

confidence: 99%

Robust Detection and Identification of Partially Occluded Circular Markers

Köhler

Pagani

Stricker

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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“…The CircleTag can be further configured to control the relative proportions of the tag that are occupied by the bullseye and data rings, giving rise to four tag shapes which may contain either template or symbolic payloads. The symbolic payload can be configured to store an arbitrary amount of data using the rotational invariance abstraction (Rice et al, 2004). Figure 1 shows four example tags.…”

Section: Cantagmentioning

confidence: 99%

Analysing fundamental properties of marker-based vision system designs

Rice

Harle

Beresford

2006

Pervasive and Mobile Computing

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This paper investigates fundamental properties of Marker-based Vision (MBV) systems. We present a theoretical analysis of the performance of basic tag designs which is extended through simulation to investigate the effects of different processing algorithms. Real-world data are processed and related to the simulated results. Image processing is performed using Cantag, an open source software toolkit for building Marker-based Vision (MBV) systems that can identify and accurately locate printed markers in three dimensions. Cantag supports multiple fiducial shapes, payload types, data sizes and image processing algorithms in one framework. This paper explores the design space of tags within the Cantag system, and describes the design parameters and performance characteristics which an application writer can use to select the best tag system for any given scenario.

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“…Tags, then, need to incorporate directionality; a problem not unique to cluster tagging. In fact the solutions proposed for the inner coding for individual tags are equally applicable here [11]. The essential principle is to use a rotationally-invariant inner code, with specific bits used to indicate direction.…”

Section: Determining the First Tag: Rotational Invariancementioning

confidence: 99%

Cluster Tagging: Robust Fiducial Tracking for Smart Environments

Harle

Hopper

2006

Location- And Context-Awareness

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Abstract. Fiducial scene markers provide inexpensive vision-based location systems that are of increasing interest to the Pervasive Computing community. Already established in the Augmented Reality (AR) field, markers are cheap to print and straightforward to locate in three dimensions. When used as a component of a smart environment, however, there are issues of obscuration, insufficient camera resolution and limited numbers of unique markers. This paper looks at the advantages of clustering multiple markers together to gain resilience to these real world problems. It treats the visual channel as an erasure channel and relevant coding schemes are applied to decode data that is distributed across the marker cluster using an algorithm that does not require each tag to be individually numbered. The advantages of clustering are determined to be a resilience to obscuration, more robust position and pose determination, better performance when attached to inconvenient shapes, and an ability to encode more than a database key into the environment. A real world example comparing the positioning capabilities of a cluster of tags with that of a single tag is presented. It is apparent that clustering provides a position estimate that is more robust, without requiring external definition of a co-ordinate frame using a database.

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Dependable Coding of Fiducial Tags

Cited by 6 publications

References 8 publications

Robust Detection and Identification of Partially Occluded Circular Markers

Robust Detection and Identification of Partially Occluded Circular Markers

Analysing fundamental properties of marker-based vision system designs

Cluster Tagging: Robust Fiducial Tracking for Smart Environments

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