Abstract: The present disclosure can obtain a high-quality composite image by determining a suitable boundary when input images are sequentially stitched together to generate the composite image. An image generating apparatus 1 generates a composite image by stitching sequentially input images together. A difference value calculating section 15 calculates difference values by using the pixel values of a reference image and the pixel values of a target image that partly overlap the reference image. The difference values represent the relative relationship between the reference image and the target image. A boundary determining section 16 determines a boundary for stitching the reference image and the target image together by using the difference values calculated by the difference value calculating section 15. Then, an image compositing section 18 generates the composite image by stitching the reference image and the target image together based on the boundary determined by the boundary determining section 16.

Abstract: An image processing device includes an input unit, a selection unit, a matching unit, an estimation unit and a merging unit. The input unit sequentially inputs images. The selection unit selects a reference image from among the input images. The matching unit calculates a correspondence relationship between a feature point of the reference image and a feature point of a target image. The estimation unit estimates an equation that causes a coordinate system of the reference image to correspond to a coordinate system of the target image using positional information of a pair of the feature points whose correspondence relationship has been calculated by the matching unit by regarding a motion between the reference image and the target image as only a rotational motion of the imaging element. The merging unit merges the input image and the target image to generate the composite image based on the equation.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: The present disclosure can obtain a high-quality composite image by determining a suitable boundary when input images are sequentially stitched together to generate the composite image. An image generating apparatus 1 generates a composite image by stitching sequentially input images together. A difference value calculating section 15 calculates difference values by using the pixel values of a reference image and the pixel values of a target image that partly overlap the reference image. The difference values represent the relative relationship between the reference image and the target image. A boundary determining section 16 determines a boundary for stitching the reference image and the target image together by using the difference values calculated by the difference value calculating section 15. Then, an image compositing section 18 generates the composite image by stitching the reference image and the target image together based on the boundary determined by the boundary determining section 16.

Abstract: The present disclosure can obtain a high-quality composite image by determining a suitable boundary when input images are sequentially stitched together to generate the composite image. An image generating apparatus 1 generates a composite image by stitching sequentially input images together. A difference value calculating section 15 calculates difference values by using the pixel values of a reference image and the pixel values of a target image that partly overlap the reference image. The difference values represent the relative relationship between the reference image and the target image. A boundary determining section 16 determines a boundary for stitching the reference image and the target image together by using the difference values calculated by the difference value calculating section 15. Then, an image compositing section 18 generates the composite image by stitching the reference image and the target image together based on the boundary determined by the boundary determining section 16.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: The present disclosure can obtain a high-quality composite image by determining a suitable boundary when input images are sequentially stitched together to generate the composite image. An image generating apparatus 1 generates a composite image by stitching sequentially input images together. A difference value calculating section 15 calculates difference values by using the pixel values of a reference image and the pixel values of a target image that partly overlap the reference image. The difference values represent the relative relationship between the reference image and the target image. A boundary determining section 16 determines a boundary for stitching the reference image and the target image together by using the difference values calculated by the difference value calculating section 15. Then, an image compositing section 18 generates the composite image by stitching the reference image and the target image together based on the boundary determined by the boundary determining section 16.

Abstract: An image processing device includes an input unit, a selection unit, a matching unit, an estimation unit and a merging unit. The input unit sequentially inputs images. The selection unit selects a reference image from among the input images. The matching unit calculates a correspondence relationship between a feature point of the reference image and a feature point of a target image. The estimation unit estimates an equation that causes a coordinate system of the reference image to correspond to a coordinate system of the target image using positional information of a pair of the feature points whose correspondence relationship has been calculated by the matching unit by regarding a motion between the reference image and the target image as only a rotational motion of the imaging element. The merging unit merges the input image and the target image to generate the composite image based on the equation.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: A moving object detecting device 1 that detects a moving object by using an image includes a motion degree obtaining portion 11 that obtains a motion degree of a pixel between image frames, a color obtaining portion 13 that obtains the color of the pixel included in the image frame, an evaluation score calculating portion 14 that calculates an evaluation score indicating a motion level of the color on the basis of the motion degree for each color obtained by the color obtaining portion, and a moving object detecting portion 15 that detects the moving object on the basis of the evaluation score for each color.

Abstract: An object detection apparatus that detects an object to be detected captured in a determination image according to a feature amount of the object to be detected preliminarily learned by the use of a learning image, the object detection apparatus including a detector 2 causing strong classifiers 21m to operate in order of lower classification accuracy, continuing processing when the strong classifier 21m has determined that the object to be detected is captured in the determination image, and determining that the object to be detected has not been detected without causing the strong classifier 21m having classification accuracy higher than the aforementioned strong classifier 21m to operate, when the strong classifier 21m has determined that the object to be detected is not captured in the determination image, wherein the strong classifier 21m inputs a classification result of the strong classifier 21m having classification accuracy lower than the aforementioned strong classifier 21m and determines whether the

Abstract: An object detection apparatus that detects an object to be detected captured in a determination image according to a feature amount of the object to be detected preliminarily learned by the use of a learning image, the object detection apparatus including a detector causing strong classifiers to operate in order of lower classification accuracy, continuing processing when the strong classifier has determined that the object to be detected is captured in the determination image, and determining that the object to be detected has not been detected without causing the strong classifier having classification accuracy higher than the aforementioned strong classifier to operate, when the strong classifier has determined that the object to be detected is not captured in the determination image, wherein the strong classifier inputs a classification result of the strong classifier having classification accuracy lower than the aforementioned strong classifier and determines whether the object to be detected is captured

Abstract: A moving object detecting device 1 that detects a moving object by using an image includes a motion degree obtaining portion 11 that obtains a motion degree of a pixel between image frames, a color obtaining portion 13 that obtains the color of the pixel included in the image frame, an evaluation score calculating portion 14 that calculates an evaluation score indicating a motion level of the color on the basis of the motion degree for each color obtained by the color obtaining portion, and a moving object detecting portion 15 that detects the moving object on the basis of the evaluation score for each color.

Abstract: An object detection apparatus that detects an object to be detected captured in a determination image according to a feature amount of the object to be detected preliminarily learned by the use of a learning image, the object detection apparatus including a detector causing strong classifiers to operate in order of lower classification accuracy, continuing processing when the strong classifier has determined that the object to be detected is captured in the determination image, and determining that the object to be detected has not been detected without causing the strong classifier having classification accuracy higher than the aforementioned strong classifier to operate, when the strong classifier has determined that the object to be detected is not captured in the determination image, wherein the strong classifier inputs a classification result of the strong classifier having classification accuracy lower than the aforementioned strong classifier and determines whether the object to be detected is captured