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1.
Sensors (Basel) ; 23(11)2023 May 24.
Article in English | MEDLINE | ID: mdl-37299770

ABSTRACT

Multimodal user interfaces promise natural and intuitive human-machine interactions. However, is the extra effort for the development of a complex multisensor system justified, or can users also be satisfied with only one input modality? This study investigates interactions in an industrial weld inspection workstation. Three unimodal interfaces, including spatial interaction with buttons augmented on a workpiece or a worktable, and speech commands, were tested individually and in a multimodal combination. Within the unimodal conditions, users preferred the augmented worktable, but overall, the interindividual usage of all input technologies in the multimodal condition was ranked best. Our findings indicate that the implementation and the use of multiple input modalities is valuable and that it is difficult to predict the usability of individual input modalities for complex systems.


Subject(s)
Technology , User-Computer Interface , Humans , Speech
2.
IEEE Trans Vis Comput Graph ; 25(11): 3105-3113, 2019 Nov.
Article in English | MEDLINE | ID: mdl-31403419

ABSTRACT

Shader lamp systems augment the real environment by projecting new textures on known target geometries. In dynamic scenes, object tracking maintains the illusion if the physical and virtual objects are well aligned. However, traditional trackers based on texture or contour information are often distracted by the projected content and tend to fail. In this paper, we present a model-based tracking strategy, which directly takes advantage from the projected content for pose estimation in a projector-camera system. An iterative pose estimation algorithm captures and exploits visible distortions caused by object movements. In a closed-loop, the corrected pose allows the update of the projection for the subsequent frame. Synthetic frames simulating the projection on the model are rendered and an optical flow-based method minimizes the difference between edges of the rendered and the camera image. Since the thresholds automatically adapt to the synthetic image, a complicated radiometric calibration can be avoided. The pixel-wise linear optimization is designed to be easily implemented on the GPU. Our approach can be combined with a regular contour-based tracker and is transferable to other problems, like the estimation of the extrinsic pose between projector and camera. We evaluate our procedure with real and synthetic images and obtain very precise registration results.

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