Abstract: In one embodiment, a method comprises receiving a stream of transport packets encapsulating media packets, and generating a reference to the point-of-interest media packet relative to the location of the point-of-interest within the transport packet stream. The reference is generated for each media packet that is identified as a point-of-interest.

Abstract: In one embodiment, a method comprises receiving a stream of transport packets encapsulating media packets, and generating a reference to the point-of-interest media packet relative to the location of the point-of-interest within the transport packet stream. The reference is generated for each media packet that is identified as a point-of-interest.

Abstract: In one embodiment, a method comprises receiving a stream of transport packets encapsulating media packets, and generating a reference to the point-of-interest media packet relative to the location of the point-of-interest within the transport packet stream. The reference is generated for each media packet that is identified as a point-of-interest.

Abstract: In one embodiment, a method comprises receiving a stream of transport packets encapsulating media packets, and generating a reference to the point-of-interest media packet relative to the location of the point-of-interest within the transport packet stream.

Abstract: A method and apparatus subsamples, in a constraint satisfying manner, an image for subsequent processing of the subsampled image. The subsampling is based on constraints provided for the subsequent image processing. A subsampling factor or pair of factors are determined for the image and the image is subsampled by the subsampling factor(s). The constraints comprise at least time constraints, uncertainty constraints, accuracy constraints or implementation constraints. When time constraints are given, the constraints specify a function of the time needed for the subsequent image processing along with at least a maximum and a minimum time that the subsequent image processing should take. When uncertainty constraints are specified, the constraints give a function of the uncertainty in the subsequent image processing and at least a maximum and a minimum uncertainty required from the subsequent image processing.

Abstract: A method and apparatus subsamples, in a constraint satisfying manner, an image for subsequent processing of the subsampled image. The subsampling is based on constraints provided for the subsequent image processing. A subsampling factor or pair of factors are determined for the image and the image is subsampled by the subsampling factor(s). The constraints comprise at least time constraints, uncertainty constraints, accuracy constraints or implementation constraints. When time constraints are given, the constraints specify a function of the time needed for the subsequent image processing along with at least a maximum and a minimum time that the subsequent image processing should take. When uncertainty constraints are specified, the constraints give a function of the uncertainty in the subsequent image processing and at least a maximum and a minimum uncertainty required from the subsequent image processing.

Abstract: An automated object inspection system involving locating an object in an input image obtains a digital representation of an image including the object. Expected geometric parameters representing expected geometric features of the object are obtained. A set of pixels required for input to an object locating process is selected. A subsampling factor is defined based upon at least the expected geometric parameters. The subsampling factor defines a reduction in resolution of the set of pixels. The set of pixels is subsampled in accordance with the defined subsampling factor. The object locating process is run on the subsampled set of pixels. In defining the subsampling factor based upon at least the expected geometric parameters, the system takes into account constraints such as time an uncertainty constraints.

Abstract: Determining the position of a generally rectangular device is achieved by performing subsampling of image data, thresholding of the subsampled data, extraction of boundary features based on the output of the thresholding, calculation of correspondence between extracted boundary features and the generally rectangular device, and a final fit against a model of the generally rectangular device. Correspondence between the boundary features of the image and the generally rectangular device is performed by locating points in the extracted boundary feature which may correspond to corners of the generally rectangular device, removing those points which correspond to known objects other than the generally rectangular device, removing those points likely to belong to unknown objects, and fitting the points to an input model of the generally rectangular device to determine its position.