Pandu Ranga Rao Devarakota

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— Static occupant classification is an important requirement in designing so-called " smart airbags ". Systems for this purpose can be either based on pressure sensors or vision sensors. Vision-based systems are advantageous over pressure sensor based systems, as they can provide additional functionalities like dynamic occupant position analysis or child(More)
The deployment of vehicle airbags for maximum protection requires information about the occupant's position, movement , weight, size etc. Specifically it is desirable to discriminate between adults, children, front-or rear faced child seats, objects put on the seat or simply empty seats. 2D images lack depth information about the object and are very(More)
This paper describes a 3-D vision system based on a new 3-D sensor technology for the detection and classification of occupants in a car. New generation of so-called " smart airbags " require the information about the occupancy type and position of the occupant. This information allows a distinct control of the airbag inflation. In order to reduce the risk(More)
Pattern classification techniques derived from statistical principles have been widely studied and have proven powerful in addressing practical classification problems. In real-world applications, the challenge is often to cope with unseen patterns i.e., patterns which are very different from those examined during the training phase. The issue with unseen(More)
In [3], a low-resolution range sensor was investigated for an occupant classification system that distinguish person from child seats or an empty seat. The optimal deployment of vehicle airbags for maximum protection moreover requires information about the occupant's size and position. The detection of occupant's position involves the detection and(More)
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