Dimensionality reduction methods are an essential tool for multidimensional data analysis, and many interesting processes can be studied as time‐dependent multivariate datasets. There are, however, few studies and proposals that leverage on the concise power of expression of projections in the context of dynamic/temporal data. In this paper, we aim at providing an approach to assess projection techniques for dynamic data and understand the relationship between visual quality and stability. Our approach relies on an experimental setup that consists of existing techniques designed for time‐dependent data and new variations of static methods. To support the evaluation of these techniques, we provide a collection of datasets that has a wide variety of traits that encode dynamic patterns, as well as a set of spatial and temporal stability metrics that assess the quality of the layouts. We present an evaluation of 9 methods, 10 datasets, and 12 quality metrics, and elect the best‐suited methods for projecting time‐dependent multivariate data, exploring the design choices and characteristics of each method. Additional results can be found in the online benchmark repository. We designed our evaluation pipeline and benchmark specifically to be a live resource, open to all researchers who can further add their favorite datasets and techniques at any point in the future.

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Abstract. The present paper describes the objectives, structure, present stage, results and future milestones of the project ELEVA. This project is aimed to control an autonomous helicopter in order to follow an overhead power cable by means of a stereo computer vision system. The helicopter is aimed to have always in sight the overhead power cable, to follow it by using it as an external visual reference guide and to record it for its ulterior visual inspection. These objectives are achieved by using a 3D computer vision system to generate the reference trajectory to be followed and by using internal sensors to control its stability and its trajectory. The paper presents the results obtained so far: visual detection and tracking of the power cable, robust under changing environments, and robust stationary control of the helicopter, now linked to a safety mechanical platform. Finally this paper describes the future challenges of the project and its temporal milestones.

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