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Although our assumption oversimplifies the general motion recognition problem, our purpose in this article is to present the idea of incorporating the PIR sensor and random compression theory into a single hardware measurement process.
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The choice of transforming the motion vector field to an energy field is justified by the observation that often the latter provides more appropriate information for motion-based recognition problems [26, 33].
Focusing on the combination of dynamic projection and interactive filtering visualization methods, AR devices in combination with motion recognition tools might solve a significant scaling problem especially for multidimensional representations that comes to this area from the field of Architecture.
However, the general motion recognition and behavior understanding should be considered the more challenging problems.
In the paper, the human action/gait recognition problem is formulated as a histogram matching problem, and a quadtree decomposition-based multiresolution structure on the motion energy histogram (MEH) is used to speed up the calculation.
The motion symbols allow motion recognition and synthesis.
Emotion recognition from speech is a pattern recognition problem.
Table 1 Results of motion recognition events Scene no.
Table 1 shows the results of a motion recognition event.
Hausdorff distance-based template matching is employed for motion recognition.
In "Climbing motion recognition", a novel motion recognition technique is presented, and we describe our experiments in "Discussion and results".
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