Download Activity Monitoring by Multiple Distributed Sensing: Second by Pier Luigi Mazzeo, Paolo Spagnolo, Thomas B. Moeslund PDF

By Pier Luigi Mazzeo, Paolo Spagnolo, Thomas B. Moeslund

This ebook constitutes the completely refereed post-conference complaints of the second one overseas Workshop on task tracking through a number of disbursed Sensing, AMMDS 2014, held in Stockholm, Sweden, in August 2014, as a satellite tv for pc occasion of ICPR 2014, the twenty second overseas convention on development reputation. The nine revised complete papers integrated within the quantity examine the demanding situations that come up whilst dispensed sensor networks are used to trace, visual display unit, and comprehend the task, rationale, and factors of humans. program parts contain human-computer interplay, person interface layout, robotic studying, and surveillance.

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Extra resources for Activity Monitoring by Multiple Distributed Sensing: Second International Workshop, AMMDS 2014, Stockholm, Sweden, August 24, 2014, Revised Selected Papers

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Recognizing interleaved and concurrent activities: a statistical-relational approach. In: Proccedings of the IEEE International Conference on Pervasive Computing and Communications (PerCom) (2011) 9. : Temporal pattern discovery for anomaly detection in a smart home. In: Proceedings of the 3rd IET Conference on Intelligent Environments (IE) (2007) 10. : Extracting places and activities from gps traces using hierarchical conditional random fields. Robot. Res. 26(1), 119–134 (2007) 11. : Activity recognition using temporal evidence theory.

It is important to point out that different kinds of bags carried by the persons, as well as the variation of position where they carry those bags, makes harder the classification, in (Fig. 7) are shown some details. Another hard situation emerges when the body occludes the bag, in this case even humans show difficulties to detect the bag. Fig. 7. CAISA-B carrying bag images. In our experimentation protocol, the 200 subjects to analyze were divided in 100 disjoint sets, each containing a person carrying a bag and a person without bag.

3D reconstructed gait sequences. Example of reconstructed gait sequences, sampled at 2 Hz, where each point represents the center of a squared voxel. 34 D. L´ opez-Fern´ andez et al. volumes along the gait sequence. The whole gait sequences can be reconstructed, as shown in Fig. 4. Then, these gait volumes are aligned and centred respect to a global reference system. After this, we can get rendered projections of these volumes to test 2D-based gait recognition algorithms. By this way, we can test view-dependent gait recognition algorithms on any kind of path, either curved or straight.

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