Sentence examples for motion detection applications from inspiring English sources

Piezoresistive strain sensors for structural health monitoring (SHM) and human body motion detection applications commonly use polymer nanocomposites based on carbon fillers such as carbon black (CB), carbon nanotubes (CNTs) or graphene nanoplatelets (GNPs).

This study sheds light on the effects of filler morphological structure on electrical conductivity and piezoresistive sensitivity of polymer nanocomposites, introducing a new strategy to prepare multifunctional polymer nanocomposites with very high piezoresistive sensitivity for SHM and body motion detection applications.

In the context of this paper we present the summary of the results obtained on a 3-case studies in the domain of real-time image processing: (i) a motion detection application,   (ii) an artificial extension of this detection application,   (iii) a robotic vision application.  . a motion detection application, an artificial extension of this detection application, a robotic vision application.

The original DFG is the model of an image processing application: motion detection on a fixed image background.

In this paper we will focus on motion pattern extraction and event detection applications.

The extremely small size also makes them good for embedded applications like motion detection, security, or eliminating driver blind spots and such.

The detection of moving objects is critical in many defense and security applications, where motion detection is usually performed in a preprocessing step, a key to the success in the following target tracking and recognition.

Table 1 shows several experiments considering as input application a motion detection algorithm used in the transmission of real-time video signals on data networks.

Indeed, we can define some criteria allowing taking into account implementation constraints such as power consumption or other limitations like the kind of targeted application for motion detection algorithm.

In this work the FRS segmentation algorithm was selected due to its proven good performance on a variety of applications (face detection, motion detection, Automatic Target Recognition (ATR)) and has been developed in a low-cost, reconfigurable computing platform, aiming at low cost applications.

Successful detection of motion helps to reduce the information redundancy in all of these applications and thus motion detection has become an active research issue.