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As reliability of mobile object attributes increases in time (becomes stable), the parallelepiped classification process can also be guided to boost the search of most likely parallelepiped configurations.
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The dynamics model is the process of computing and updating the attributes of a mobile object, considering previous information and current observations.
In the context of tracking, a hypothesis corresponds to a set of mobile objects representing a possible configuration, given previously estimated object attributes (e.g. width, length, velocity) and new incoming visual evidence (blobs at current frame).
This way, the value pm for a mobile object m will mostly consider the probability values for attribute groups with higher reliability, using the values that can be trusted the most.
mobile object.
mobile object detected.
While some attributes like measurements are typically unambiguous and can be recognized without context, object attributes require a resolving object context.
The structure of the template includes the following main fields: Regular Expression, Dictionaries, Relations, Object Attributes and Relation Attributes.
Both flow around immobile objects and the translation and rotation of mobile objects are considered.
Mobile Objects (e.g. panel paintings, easel paintings).
The use of Singhal and Shukla's [35] mobile network object generator is based on 10,000 generation mobile objects.
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