Fourier tags: Smoothly degradable fiducial markers for use in human-robot interaction

Sattar, Junaed; Bourque, Élyse; Giguère, Philippe; Dudek, Gregory

doi:10.1109/crv.2007.34

Cited by 54 publications

(31 citation statements)

References 5 publications

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“…Techniques for zooming into visual encodings include recursive grids of barcodes [21] and nested barcodes [27]. Fourier tags [23] handle the opposite case of zooming out: at close distance, they can be completely decoded, but as the camera zooms out, fewer bits can be decoded; low-order bits are lost before high-order bits.…”

Section: Related Workmentioning

confidence: 99%

EyeDecrypt — Private Interactions in Plain Sight

Forte

Garay

Jim

et al. 2014

Lecture Notes in Computer Science

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We introduce EyeDecrypt, a novel technology for privacy-preserving human-computer interaction. EyeDecrypt allows only authorized users to decipher data shown on a display, such as an electronic screen or plain printed material; in the former case, the authorized user can then interact with the system (e.g., by pressing buttons on the screen), without revealing the details of the interaction to others who may be watching or to the system itself.The user views the decrypted data on a closely-held personal device, such as a pair of smart glasses with a camera and heads-up display, or a smartphone. The data is displayed as an image overlay on the personal device, which we assume cannot be viewed by the adversary. The overlay is a form of augmented reality that not only allows the user to view the protected data, but also to securely enter input into the system by randomizing the input interface.EyeDecrypt consists of three main components: a visualizable encryption scheme; a dataglyphbased visual encoding scheme for the ciphertexts generated by the encryption scheme; and a randomized input and augmented reality scheme that protects user inputs without harming usability. We describe all aspects of EyeDecrypt, from security definitions, constructions and analysis, to implementation details of a prototype developed on a smartphone.

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Section: Related Workmentioning

confidence: 99%

EyeDecrypt — Private Interactions in Plain Sight

Forte

Garay

Jim

et al. 2014

Lecture Notes in Computer Science

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“…The ARToolkit marker system [8] consists of symbols very similar to the ARTag flavor in that they contain different patterns enclosed within a square black border. Circular markers are also possible in fiducial schemes, as demonstrated by the Fourier Tags [9] fiducial system. Gesture-based robot control has been considered extensively in Human-Robot Interaction (HRI).…”

Section: Background and Related Workmentioning

confidence: 99%

Towards quantitative modeling of task confirmations in human-robot dialog

Sattar

Dudek

2011

2011 IEEE International Conference on Robotics and Automation

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Abstract-We present a technique for robust human-robot interaction taking into consideration uncertainty in input and task execution costs incurred by the robot. Specifically, this research aims to quantitatively model confirmation feedback, as required by a robot while communicating with a human operator to perform a particular task. Our goal is to model human-robot interaction from the perspective of risk minimization, taking into account errors in communication, risk involved in performing the required task, and task execution costs. Given an input modality with non-trivial uncertainty, we calculate the cost associated with performing the task specified by the user, and if deemed necessary, ask the user for confirmation. The estimated task cost and the uncertainty measure is given as input to a Decision Function, the output of which is then used to decide whether to execute the task, or request clarification from the user. In cases where the cost or uncertainty (or both) is estimated to be exceedingly high by the system, task execution is deferred until a significant reduction in the output of the Decision Function is achieved. We test our system through human-interface experiments, based on a framework custom designed for our family of amphibious robots, and demonstrate the utility of the framework in the presence of large task costs and uncertainties. We also present qualitative results of our algorithm from field trials of our robots in both open-and closed-water environments.

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“…Similarly, artificial features can make it possible to evaluate Simultaneous Localization and Mapping (SLAM) algorithms under controlled algorithms [8]. Robotics applications have led to the development of additional tag detection systems [9], [10].…”

Section: Introductionmentioning

confidence: 99%

AprilTag: A robust and flexible visual fiducial system

Olson

2011

2011 IEEE International Conference on Robotics and Automation

1,362

721

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Abstract-While the use of naturally-occurring features is a central focus of machine perception, artificial features (fiducials) play an important role in creating controllable experiments, ground truthing, and in simplifying the development of systems where perception is not the central objective.We describe a new visual fiducial system that uses a 2D bar code style "tag", allowing full 6 DOF localization of features from a single image. Our system improves upon previous systems, incorporating a fast and robust line detection system, a stronger digital coding system, and greater robustness to occlusion, warping, and lens distortion. While similar in concept to the ARTag system, our method is fully open and the algorithms are documented in detail.

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Fourier tags: Smoothly degradable fiducial markers for use in human-robot interaction

Cited by 54 publications

References 5 publications

EyeDecrypt — Private Interactions in Plain Sight

EyeDecrypt — Private Interactions in Plain Sight

Towards quantitative modeling of task confirmations in human-robot dialog

AprilTag: A robust and flexible visual fiducial system

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