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In a lot of multi-Kinect V2-based systems, the registration of these Kinect V2 sensors is an important step which directly affects the system precision. The coarse-to-fine method using calibration objects is an effective way to solve the Kinect V2 registration problem. However, for the registration of Kinect V2 cameras with large displacements, this kind of method may fail. To this end, a novel Kinect V2 registration method, which is also based on the coarse-to-fine framework, is proposed by using camera and scene constraints.

This paper presents a novel method to track the hierarchical structure of Web video groups on the basis of salient keyword matching including semantic broadness estimation. To the best of our knowledge, this paper is the first work to perform extraction and tracking of the hierarchical structure simultaneously. Specifically, the proposed method first extracts the hierarchical structure of Web video groups and salient keywords of them on the basis of an improved scheme of our previously reported method.

Gait analysis is often used as part of the rehabilitation program for post-stoke recovery assessment. Since current optical diagnostic and patient assessment tools tend to be expensive and not portable, this paper proposes a novel marker-based tracking system using a single depth camera which provides a cost-effective solution suitable for home and clinic use. The proposed system can simultaneously generate motion patterns even within a complex background using the proposed geometric model-based algorithm and autonomously provide gait analysis results.