Algorithms for the selection of the active sensors in distributed tracking: comparison between Frisbee and GNS methods.
Agostino CapponiConcetta PilottoGiovanni GolinoAlfonso FarinaLance M. KaplanPublished in: FUSION (2006)
Keyphrases
- optimization methods
- significant improvement
- computational cost
- machine learning methods
- benchmark datasets
- machine learning algorithms
- experimental comparison
- real time
- synthetic and real datasets
- computationally intensive
- methods require
- methods outperform
- computational complexity
- computationally expensive
- search methods
- complexity analysis
- preprocessing
- high computational complexity
- particle filter
- data structure
- learning algorithm
- heuristic methods
- sensor fusion
- computationally demanding
- challenging sequences
- low cost sensors
- camera network
- problems in computer vision
- peer to peer
- distributed systems
- optimization problems
- worst case
- motion estimation
- multi agent
- computer vision
- machine learning