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This paper presents an adaptive sparse sampling approach based on mobile robotic sensors. Traditionally, the sampling methods collect measurements without considering possible distributions of target signals. In this paper a feedback driven algorithm is discussed, where new measurements are determined based on the analysis of existing observations under a sparse domain. More specifically, Wavelet...
This paper presents a novel approach, compressive mobile sensing, to use mobile sensors to sample and reconstruct sensing fields based on compressive sensing. Compressive sensing is an emerging research field based on the fact that a small number of linear measurements can recover a sparse signal without losing any useful information. Using compressive sensing, the signal can be recovered by a sampling...
A new general 3D object model is required in the literature of smart camera networks to facilitate future research. This paper presents a novel hierarchical and structural 3D model description which is well-suited for both events detection and real-time free view-point surveillance. With this 3D model, sparse points are used to reconstruct objects. In addition, the state of the model is easy to track...
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