Abstract: The present invention provides a speech recognition processing system in which speech recognition processing is executed parallelly by plural speech recognizing units. Before text data as the speech recognition result is output from each of the speech recognizing units, information indicating each speaker is parallelly displayed on a display in emission order of each speech. When the text data is output from each of the speech recognizing units, the text data is associated with the information indicating each speaker and the text data is displayed.

Abstract: The present invention provides a speech recognition processing system in which speech recognition processing is executed parallelly by plural speech recognizing units. Before text data as the speech recognition result is output from each of the speech recognizing units, information indicating each speaker is parallelly displayed on a display in emission order of each speech. When the text data is output from each of the speech recognizing units, the text data is associated with the information indicating each speaker and the text data is displayed.

Abstract: A pose estimation and comparison system has a pose estimation and comparison unit. The pose estimation and comparison unit has an pose candidate decision unit which decides an pose candidate. According to the generated pose candidate, a comparison image generation unit generates a plurality of comparison images close to the input image, while projecting a three-dimensional object model obtained from a three-dimensional object model storage unit to a two-dimensional image. A sharpness extraction unit extracts a first sharpness amount reflecting the sharpness from each of the generated comparison images. A weighted difference calculator calculates a plurality of weighted differences by weighting the first sharpness amount to the difference between the input image and each of the comparison images. A determination unit selects a comparison image having the smallest weighted difference as the comparison image closest to the input image, thereby performing the pose estimation and comparison.

Abstract: Even when only a small number of reference images are available for each object, it is possible to search at high speed a reference image stored in a database from an input image of an object imaged with a different pose and a different illumination condition. A reference image matching result storage section (50) inputs reference images from a reference image storage section (70) and stores in advance results of matching of the input images with representative 3-dimensional object models of a representative 3-dimensional object model storage section (20). According to each representative 3-dimensional object model, image generation means (30) generates a comparison image having an input condition similar to the input image obtained from the image input means (10). Image matching means (40) calculates similarity between the input image and the image generated.

Abstract: There are provided a three-dimensional data input means (10) for input the three-dimensional data of an object, a reference image storing unit (30) for storing a reference image of at least one object, a pose candidate deciding means (20) for generating a pose candidate that is a candidate for the pose of the object, a comparison image generating means (40) for generating a comparison image close to the reference image while projecting the three-dimensional data onto a two-dimensional image in accordance with the pose candidate, and an image comparing means (55) for performing comparison based on either a distance value or similarity degree between the reference image and the comparison image. This allows comparison or search to be performed with high accuracy even when the reference image of the object is captured under different conditions such as pose and illumination, even when no three-dimensional object model of the object can be obtained in advance, or even when only one or few reference images exist.

Abstract: An object pose estimating and matching system is disclosed for estimating and matching the pose of an object highly accurately by establishing suitable weighting coefficients, against images of an object that has been captured under different conditions of pose, illumination. Pose candidate determining unit determines pose candidates for an object. Comparative image generating unit generates comparative images close to an input image depending on the pose candidates, based on the reference three-dimensional object models. Weighting coefficient converting unit determines a coordinate correspondence between the standard three-dimensional weighting coefficients and the reference three-dimensional object models, using the standard three-dimensional basic points and the reference three-dimensional basic points, and converts the standard three-dimensional weighting coefficients into two-dimensional weighting coefficients depending on the pose candidates.

Abstract: Even when only a small number of reference images are available for each object, it is possible to search at high speed a reference image stored in a database from an input image of an object imaged with a different pose and a different illumination condition. A reference image matching result storage section (50) inputs reference images from a reference image storage section (70) and stores in advance results of matching of the input images with representative 3-dimensional object models of a representative 3-dimensional object model storage section (20). According to each representative 3-dimensional object model, image generation means (30) generates a comparison image having an input condition similar to the input image obtained from the image input means (10). Image matching means (40) calculates similarity between the input image and the image generated.

Abstract: Even when only a small number of reference images are available for each object, it is possible to search at high speed a reference image stored in a database from an input image of an object imaged with a different pose and a different illumination condition. A reference image matching result storage section (50) inputs reference images from a reference image storage section (70) and stores in advance results of matching of the input images with representative 3-dimensional object models of a representative 3-dimensional object model storage section (20). According to each representative 3-dimensional object model, image generation means (30) generates a comparison image having an input condition similar to the input image obtained from the image input means (10). Image matching means (40) calculates similarity between the input image and the image generated.

Abstract: An pose estimation and comparison system has an pose estimation and comparison unit (20). The pose estimation and comparison unit (20) has an pose candidate decision unit (30) which decides an pose candidate. According to the generated pose candidate, a comparison image generation unit (40) generates a plurality of comparison images close to the input image, while projecting a three-dimensional object model obtained from a three-dimensional object model storage unit (45) to a two-dimensional image. A sharpness extraction unit (60) extracts a first sharpness amount reflecting the sharpness from each of the generated comparison images. A weighted difference calculator (50) calculates a plurality of weighted differences by weighting the first sharpness amount to the difference between the input image and each of the comparison images.

Abstract: There are provided a three-dimensional data input means (10) for input the three-dimensional data of an object, a reference image storing unit (30) for storing a reference image of at least one object, a pose candidate deciding means (20) for generating a pose candidate that is a candidate for the pose of the object, a comparison image generating means (40) for generating a comparison image close to the reference image while projecting the three-dimensional data onto a two-dimensional image in accordance with the pose candidate, and an image comparing means (55) for performing comparison based on either a distance value or similarity degree between the reference image and the comparison image. This allows comparison or search to be performed with high accuracy even when the reference image of the object is captured under different conditions such as pose and illumination, even when no three-dimensional object model of the object can be obtained in advance, or even when only one or few reference images exist.

Abstract: An object pose estimating and matching system is disclosed for estimating and matching the pose of an object highly accurately by establishing suitable weighting coefficients, against images of an object that has been captured under different conditions of pose, illumination. Pose candidate determining unit determines pose candidates for an object. Comparative image generating unit generates comparative images close to an input image depending on the pose candidates, based on the reference three-dimensional object models. Weighting coefficient converting unit determines a coordinate correspondence between the standard three-dimensional weighting coefficients and the reference three-dimensional object models, using the standard three-dimensional basic points and the reference three-dimensional basic points, and converts the standard three-dimensional weighting coefficients into two-dimensional weighting coefficients depending on the pose candidates.

Abstract: Even when only a small number of reference images are available for each object, it is possible to search at high speed a reference image stored in a database from an input image of an object imaged with a different pose and a different illumination condition. A reference image matching result storage section (50) inputs reference images from a reference image storage section (70) and stores in advance results of matching of the input images with representative 3-dimensional object models of a representative 3-dimensional object model storage section (20). According to each representative 3-dimensional object model, image generation means (30) generates a comparison image having an input condition similar to the input image obtained from the image input means (10). Image matching means (40) calculates similarity between the input image and the image generated.

Abstract: A character strings reading device for reading character strings from input image data comprises cut-out recognition means for cutting out a segment corresponding to one character from the image data to perform individual character recognition every segment, a recognition result buffer for storing a recognition result of the cut-out recognition means, word searching means for searching a word string candidate corresponding to a combination of character candidates in the recognition result buffer, a word string candidate buffer for storing a search result of the word searching means, check portion determining means for determining a check target portion and a presumed character string of the check target portion on the basis of the result in the word string candidate buffer, and check means for judging the possibility of existence of the presumed character string on the check portion.