Empowering UAV scene perception by semantic spatio-temporal features

@article{Cavaliere2018EmpoweringUS,
  title={Empowering UAV scene perception by semantic spatio-temporal features},
  author={Danilo Cavaliere and Alessia Saggese and Sabrina Senatore and Mario Vento and Vincenzo Loia},
  journal={2018 IEEE International Conference on Environmental Engineering (EE)},
  year={2018},
  pages={1-6}
}
The use of unmanned aerial vehicles (UAVs) is becoming a key asset in different application domains: from the military to surveillance tasks; to filming and journalism to shipping and delivery; to disaster monitoring to rescue operation and healthcare. One of the most desirable UAV capabilities is a human-like scenario understanding, i.e., the object recognition and interactions with other objects and with the environment, through the scene evolution, in order to get a high-view scenario… CONTINUE READING

Citations

Publications citing this paper.

Towards an agent-driven scenario awareness in remote sensing environments

  • 2018 IEEE Symposium Series on Computational Intelligence (SSCI)
  • 2018
VIEW 1 EXCERPT
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 25 REFERENCES

Effective Quality-Aware Sensor Data Management

  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • 2018
VIEW 1 EXCERPT

A knowledge-based approach for video event detection using spatio-temporal sliding windows

  • 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
  • 2017
VIEW 1 EXCERPT

Image Piece Learning for Weakly Supervised Semantic Segmentation

  • IEEE Transactions on Systems, Man, and Cybernetics: Systems
  • 2017
VIEW 1 EXCERPT

Object Tracking Benchmark

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2015
VIEW 1 EXCERPT