Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Estimating the location of people using a network of sensors placed throughout an environment is a fundamental challenge in smart environments and ubiquitous computing. Id-sensors such as infrared badges provide explicit object identity information but coarse location information while anonymous sensors such as laser range-finders provide accurate location information only. Tracking using both sensor types simultaneously is an open research challenge.  present a novel approach to tracking multiple objects that combines the accuracy benefits of anonymous sensors and the identification certainty of id-sensors. Rao-Blackllised particle filters are used to estimate object locations. Each particle represents the association history beten Kalman filtered object tracks and observations. After using only anonymous sensors until id estimates are certain enough, id assignments are sampled as ll resulting in a fully Rao-Blackllised particle filter over both object tracks and id assignments. Our approach was implemented and tested successfully using data collected in an indoor environment.
['Dirk Schulz', 'Dieter Fox', 'Jeffrey Hightower']
I am writing a research paper on a idea People tracking with anonymous and ID-sensors using Rao-Blackwellised particle filters
[{"from": "human", "value": "I am writing a research paper on a idea People tracking with anonymous and ID-sensors using Rao-Blackwellised particle filters"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Estimating the location of people using a network of sensors placed throughout an environment is a fundamental challenge in smart environments and ubiquitous computing. Id-sensors such as infrared badges provide explicit object identity information but coarse location information while anonymous sensors such as laser range-finders provide accurate location information only. Tracking using both sensor types simultaneously is an open research challenge.  present a novel approach to tracking multiple objects that combines the accuracy benefits of anonymous sensors and the identification certainty of id-sensors. Rao-Blackllised particle filters are used to estimate object locations. Each particle represents the association history beten Kalman filtered object tracks and observations. After using only anonymous sensors until id estimates are certain enough, id assignments are sampled as ll resulting in a fully Rao-Blackllised particle filter over both object tracks and id assignments. Our approach was implemented and tested successfully using data collected in an indoor environment."}]