Abstract: A method for calibrating a vehicular vision system includes providing a camera at a vehicle, with the camera having a field of view. Images are captured with the camera and a set of resultant images are acquired for a classification. Information is extracted related to image features in the set of resultant images, and an appropriate subset of coefficients is determined. For each classification, a classification vector of at least one appropriate weight is stored that corresponds to the determined subset of coefficients. The determined subset of coefficients is determined by processing sets of coefficients produced from a selection of calibration images and determining a subset of coefficients which acceptably discriminate between defined classifications. A set of resultant images is acquired by limiting the dynamic range of acquired images to obtain resultant images that include at least one region of interest.

Abstract: A method for calibrating a vehicular vision system includes providing a camera at a vehicle, with the camera having a field of view. Images are captured with the camera and a set of resultant images are acquired for a classification. Information is extracted related to image features in the set of resultant images, and an appropriate subset of coefficients is determined. For each classification, a classification vector of at least one appropriate weight is stored that corresponds to the determined subset of coefficients.

Abstract: A method for calibrating a vehicular vision system includes providing a camera at a vehicle, with the camera having a field of view. Images are captured with the camera and a set of resultant images are acquired for a classification. Information is extracted related to image features in the set of resultant images, and an appropriate subset of coefficients is determined. For each classification, a classification vector of at least one appropriate weight is stored that corresponds to the determined subset of coefficients.

Abstract: A vehicle interior classification system and method determines a classification relating to the interior of the vehicle, such as the occupancy status of a vehicle seat or the state of alertness of a vehicle driver, from one or more images of an appropriate portion of the interior of the vehicle acquired with an image capture device. The acquired images may be processed to limit the dynamic range of the images to obtain a resultant image that includes one or more regions of interest which are less than the total field of view of the image capture device. The resultant images are processed to extract information about features in the image. The set of coefficients produced with suchprocessing can be reduced to a subset of the total number of coefficients, the members of the subset being selected for their ability to discriminate between the classifications defined for the system.

Abstract: A vehicle interior classification system and method in accordance with the present invention determines a classification relating to the interior of the vehicle, such as the occupancy status of a vehicle seat or the state of alertness of a vehicle driver, from one or more images of an appropriate portion of the interior of the vehicle acquired with an image capture device. The acquired images are preferably processed to limit the dynamic range of the images to obtain a resultant image which can comprise one or more regions of interest which are less than the total field of view of the image capture device. The resultant images are processed to extract information about features in the image and, in one embodiment, this processing is achieved with a two-dimensional complex discrete wavelet transform which produces a set of coefficients corresponding to the presence and/or location of the features in the resultant image.