Canon Kabushiki Kaisha

Motorola Corporation

Jing Wu

Alison Joan Lennon

Sammy Chan

Xing Zhang

John Richard Windle

Sue-Ken Yap

Julie Rae Kowald

Ernest Yiu Cheong Wan

Khanh Phi Van Doan

Lena Qian

Nicole Ai Ling Lam

Daniel John Lloyd-Jones

Joshua Brendon Worrill

Igor Kharitonenko

Timothy Charles Edgoose

A query system () is formed by a wizard () operating to form a data server () arranged to serve data from a data source () to a client application (), each of the wizard, the client application, the data server and the data source being linked by a communications network (). The data source has native data types and data arranged in a data structure. The wizard operates to firstly identify the data source over the network. The wizard further provides an application program for traversing and examining at least one of the data structure and data of the identified data source. The application program is operable to generate a representative schema () comprising mapping data for converting the native data types to predetermined data types of a common data model. The wizard further operates to create a server application () adapted to use the representative schema to convert the data from the native data types to the predetermined data types and to serve the data to the client application according to the common data model over the network. The representative schema and the server application thereby form the data server generated by the wizard. Once formed, the data server may receive and respond to queries from the client application, which may have no knowledge of the native data types, but which are directed to the data source.

Method of generating data servers for heterogeneous data sources

A method of establishing at least one variable of a new view of data, is disclosed where the variable is obtained from at least one data source (-). The method identifies at least one display type (, FIG.), each display type having at least one corresponding template of data to be used by the new view of data. The template includes a plurality of data component slots (-) related according to the semantics of the identified display type. One or more data components to be included in the view of data are then identified, each identified data component being associated () with a slot in the template. A list of recommendations is then formed for one or more unspecified data components of the new view of data, the recommendations being based on the semantics of the display type and the identified data components. Finally at least one data component from the list of recommendations is identified as a variable for said new view of data. Also disclosed is a method of learning unknown relationships among data components across a plurality of heterogeneous data sources, and a method for recommending relevant data components for view creation across a plurality of heterogeneous data sources.

Method of using recommendations to visually create new views of data across heterogeneous sources

Access to heterogeneous data sources may be obtained by interactively determining transformations for use in mapping at least one source data component from at least one data source to a target data component. Selection of at least one the source data component is detected. A corresponding list of representative data examples is generated for each selected source data component. A resulting list of representative data examples is compiled for the target data component from the lists of representative data examples of the selected source data components, the resulting list of data examples being representative of the target data component. A modification of an example is identified from the resulting list of examples representative of the target data component, the example being modified as a single textual entity. At least one transformation is determined, by inferring from the modified example, to be applied to at least one source data component.

Methods for interactively defining transforms and for generating queries by manipulating existing query data

A method of extracting key frames from a video sequence, which video sequence includes MPEG compressed video data having block motion vectors. The method initially partially decompresses () the MPEG compressed video data to obtain block motion vectors and converts () the block motion vectors to forward block motion vectors. The method then generates () global motion signals and generates () dominant global direction clusters. The method then selects () potential key frames of the video sequence using the generated dominant global direction clusters. The method lastly decompresses () the selected key frames to obtain the extracted key frames.

Extracting key frames from a video sequence

A method () is disclosed for producing, using a multi-slot presentation skeleton (), an image presentation from a set of source images (). The method comprises establishing a duration of the presentation, an average slot duration, and based upon slot template rules, locations and properties of key slots in the skeleton (). The method then generates () candidate groups of sub-image sets from the set of source images, and selects () sub-image sets from the candidate groups for the key slots. The method then fills () the non-key slots with sub-image sets from the candidate groups, and processes () the sub-image sets in the skeleton slots using effect and transition rules, to thereby form the image presentation.

Method of automatic production of image presentations

A method of extracting key frames from a video sequence, which video sequence comprises MPEG compressed video data having block motion vectors. The method initially partially decompresses () the MPEG compressed video data to obtain block motion vectors and converts () the block motion vectors to forward block motion vectors. The method then generates () global motion signals and generates () dominant global direction clusters. The method then selects () potential key frames of the video sequence using the generated dominant global direction clusters. The method lastly decompresses () the selected key frames to obtain the extracted key frames.

A method and apparatus for determining a texture which best matches an image ( ) are provided. The method involves determination of an image feature value from the image ( ), and determination of corresponding texture feature values for each member of a set of textures ( ). Thereafter the image feature value is compared with the corresponding texture feature values of each member of the set of textures ( ) to produce comparison values, from which the best comparison value is selected according to a rule. This best comparison value determines the coresponding desired matching texture.

Texture advisor

A method for identifying one or more image frames ( ) from a series ( ) of video image frames, in order to print, store or flag the selected frames. The method calculates a gradient value for each image frame in a video shot ( ) series, identifies one or more gradient value peaks ( ) in a corresponding range of a raw data series ( ), and selects the image frames ( ) corresponding to the identified gradient value peaks. Two types of frames ( ) are identified as being suitable for printing. A first type ( ) comprises frames with a high gradient content, where the image is sharply defined. A second type of frame ( ) also has good focus, but is representative of periods of relative stillness, or lack of motion between consecutive image frames ( ) during the video shot series ( ).

Method of identifying image frames suitable for printing

The method first segments both images into homogeneous regions ( A) and assigns ( A) semantic labels (such as &ldquo;sky&rdquo;, &ldquo;cloud&rdquo;, &ldquo;water&rdquo;, &ldquo;foliage&rdquo; etc) to the homogeneous regions to describe the content of the regions using a probabilistic method. This process also results in each assigned label for a region having an associated probability value expressing the confidence level of the label being correctly assigned The method then computes ( ) a distance metric which averages over all corresponding pixels in the two images a value which is the product of a predetermined semantic difference between the assigned labels at the corresponding pixels and a weighting function which is derived from the associated probability values of the labels for each of the corresponding pixels. The semantic difference reflects similarities between the labels. For example, the semantic difference of the label pair &ldquo;sky&rdquo; and &ldquo;foliage&rdquo; is higher than the semantic difference between the more similar &ldquo;sky&rdquo; and &ldquo;cloud&rdquo; label pair. The method then compares ( ) the distance metric value with a predetermined threshold value in order to determine the similarity of the images.

Method and apparatus for computing the similarity between images

A method for reducing blurring associated with objects forming part of a grey scale image. The method includes receiving ( ) a set of image pixels and then calculating ( ) a gradient value for each one of the image pixels in the set. A selecting step ( ) selects candidate object edge pixels from the image pixels by comparing the gradient value for each one of the image pixels in the set with a threshold value. A determining step ( ) then determines a distribution of number candidate object edge pixels with specific grey level values. Thereafter, candidate object edge pixels within said distribution that have the same grey level values are identically non-linearly modified at a modifying step

Method for reducing image blurring

A method of determining image representative colors for an image comprising a plurality of image elements having color information associated therewith. Initially, the image elements are grouped into a plurality of image element groups on the basis of their colors. An initial representative color is then generated for each of the image element groups, the initial representative colors subsequently being clustered together into color clusters in a color space. Finally, an image representative color is determined based on each respective color cluster. Also shown is a method of using one or more of the image representative colors as a basis for providing one or more aesthetic color suggestions for a given image. A set of color selection rules is provided, and an aesthetic color suggested on the basis thereof.

Color adviser

A method (,) for automatically focusing an optical instrument (,) having a lens (,) with only two focus positions. The method comprises acquiring a first image (,) when the lens (,) is in a first position (,) and thereafter processing pixel light intensities (,) of part of the image to provide a focus detection value indicative of image blurr. A threshold test (,) is then effected and if the focus detection value is outside a desired range the lens (,) is automatically moved to a second position (,).

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Carlingford, Australia

Jing Wu