Iterative Local Model Selection for tracking and mapping

Iterative Local Model Selection for tracking and mapping

<p>The past decade has seen great progress in research on large scale mapping and perception in static environments. Real world perception requires handling uncertain situations with multiple possible interpretations: e.g. changing appearances, dynamic objects, and varying motion models. These...

Полное описание

Библиографические подробности
Главный автор: Segal, A
Другие авторы: Reid, I
Формат: Диссертация
Язык:English
Опубликовано: 2014
Предметы:
Probability
Robotics
Computer science (mathematics)
Stochastic processes
Artificial Intelligence
Image understanding
Information engineering
Probability theory and stochastic processes
Pattern recognition (statistics)
Sensors
Vehicle guidance (information eng)
Applications and algorithms

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