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To reveal and leverage the correlated and complemental information between different views, a great amount of multi-view learning algorithms have been proposed in recent years. However, unsupervised feature selection in multi-view learning is still a challenge due to lack of data labels that could be utilized to select the discriminative features. Moreover,(More)
Estimating 3D pose similarity is a fundamental problem on 3D motion data. Most previous work calculates L2-like distance of joint orientations or coordinates, which does not sufficiently reflect the pose similarity of human perception. In this paper, we present a new pose distance metric. First, we propose a new rich pose feature set called Geometric Pose(More)
— An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a comparison between global and local time-frequency features. The originality is to make use of a family of stationary surrogates for defining the null hypothesis of stationarity(More)
—A method is proposed for obtaining time-frequency distributions of chirp signals embedded in nonstationary noise, with the twofold objective of a sharp localization for the chirp components and a reduced level of statistical fluctuations for the noise. The technique consists in combining time-frequency reassignment with multitapering, and two variations(More)
We studied the role of the competence of an interface agent that helped users to learn and use a text editor. Participants in the study made a set of changes to a document with the aid of one of four interface agents. The agent would respond to participantsý spoken questions as well as make proactive suggestions using a synthesized voice. The agents(More)
Creating an artifact that captures the story or memory from a large photo collection is a difficult task, because the tools available are either too difficult to learn, or oversimplified to the point that they lack flexibility. Individual techniques have been developed to automate parts of the selection-editing-composition cycle, but relatively little has(More)
This research examined the ability of an anthropomorphic interface assistant to help people learn and use an unfamiliar text-editing tool, with a specific focus on assessing proactive assistant behavior. Participants in the study were introduced to a text editing system that used keypress combinations for invoking the different editing operations.(More)