Abstract: An image processing apparatus that is capable of improving subject detection accuracy with respect to image signals is disclosed. The image processing apparatus applies subject detection processing to an image by using a learning model generated based on machine learning. The image processing apparatus selects the learning model from a plurality of learning models stored in advance, in accordance with characteristics of the image to which the subject detection processing is to be applied.

Abstract: The support device has a mount part 10 for mounting an electronic device, a pair of support leg parts 20, and a pair of cross brace parts 30. The electronic device 600 when mounted on the mount part 10 is supported so as to be slanted rearward. The two support leg parts of the pair of support leg parts 20 are each provided with multiple receiving seats capable of receiving an anchor part of a cross brace part 30 and multiple bowl-shaped hole parts corresponding to the multiple receiving seats. The two cross brace parts of the pair of the cross brace parts 30 are each provided with a biasing stud having a semispherical tip, and when an anchor part is received by any of the receiving seats of the pair of support leg parts 20, the stud enters the bowl-shaped hole part corresponding to the receiving seat.

Abstract: A document size detecting apparatus includes a first acquisition unit, a second acquisition unit, and a detector. The first acquisition unit acquires a first image that is an image of an entire document as a reading target. The second acquisition unit acquires a second image that is an image of a part of the document read by a first reading apparatus. The detector detects a size of the document using a result of a matching process between the first image and the second image and a read size that is a size of the second image read by the first reading apparatus.

Abstract: A subject tracking apparatus is configured to track a subject in continuously obtained photographic images. In the photographic image, a position of the subject in the photographic image and reliability that represents subject probability are obtained. The position of the subject to a target position in the photographic image is moved a tracking state of the subject is changed on a basis of the reliability.

Abstract: The support device has a mount part 10 for mounting an electronic device, a pair of support leg parts 20, and a pair of cross brace parts 30. The electronic device 600 when mounted on the mount part 10 is supported so as to be slanted rearward. The two support leg parts of the pair of support leg parts 20 are each provided with multiple receiving seats capable of receiving an anchor part of a cross brace part 30 and multiple bowl-shaped hole parts corresponding to the multiple receiving seats. The two cross brace parts of the pair of the cross brace parts 30 are each provided with a biasing stud having a semispherical tip, and when an anchor part is received by any of the receiving seats of the pair of support leg parts 20, the stud enters the bowl-shaped hole part corresponding to the receiving seat.

Abstract: An image processing apparatus capable of accurate area tracking, and a method for controlling the same are provided. An image area for extracting a feature amount is identified based on a specified position. A plurality of images are searched for an image that corresponds to the image area using the feature amount extracted from the identified image area. The image area is identified using distance information if distance information that satisfies a reliability condition has been obtained regarding an area that includes the specified position, and without using the distance information if the distance information that satisfies the reliability condition has not been obtained.

Abstract: In an object tracking device that obtains image data, detects an object, and tracks a target object, a matching unit collates image data of a characteristic model that represents a tracking object, which is a tracking target, with input image data, and outputs a candidate region of the tracking object. An object region determination unit determines an object region from the candidate region that is output by the matching unit. A depth map calculation unit calculates depth information relating to the input image. An object depth setting unit obtains the object region that has been determined by the object region determination unit in the past and the depth information that has been calculated by the depth map calculation unit, and sets a predetermined depth range where the object can exist.

Abstract: A disclosed image processing apparatus calculates a background vector expressing a motion of a background based on a plurality of motion vectors detected between a plurality of images. Then the image processing apparatus detects a motion vector of a moving object from the plurality of motion vectors, based on a magnitude of Euclidean distance between each of the plurality of motion vectors and the background vector.

Abstract: An image processing apparatus comprises a detection circuit that, by referencing dictionary data acquired by machine learning corresponding to a target photographic subject to be detected in an obtained image, detects the target photographic subject; a selection unit that selects one of a plurality of dictionary data items corresponding to the target photographic subject; and a control circuit that, in a case where a detection evaluation value in a case where the photographic subject is detected by using the dictionary data selected by the selection unit is lower than a predetermined value, controls the detection circuit to detect the target photographic subject by using the selected dictionary data and dictionary data different to the selected dictionary data.

Abstract: An information processing apparatus includes an acquisition unit that acquires a designated color which is designated as a color, which is converted into a specific color, of a pixel among pixels which express an image, a determination unit that determines whether or not a common color area, which is expressed by pixels in a common hue range, expresses prescribed information in the image, and a conversion unit that performs a first conversion process of converting a pixel corresponding to the acquired designated color into a specific color in the common color area which is determined to express the information, and performs a second conversion process of converting a pixel corresponding to a color in a wider hue range than the designated color into a specific color in the common color area which is determined to not express the information.

Abstract: An information processing apparatus includes a recognition unit that recognizes an object which is included in an image and is expressed using a single color, and a conversion unit that performs conversion on a pixel, which is included in the image and corresponds to a designated color, into a specific color, and, in a case where a color of an area, which is in contact with an outer edge of the recognized object, is designated and a difference between the color of the recognized object and the specific color is smaller than a first reference, performs conversion on a pixel of the outer edge into a color other than the specific color.

Abstract: In a focus adjusting apparatus, a tracking unit detects from an image signal an area of a subject to be tracked, a position of an imaging plane of the area and reliability of the position, and a prediction unit predicts a position of an imaging plane when the image signal was obtained based on a history of detected positions of imaging planes. A setting unit sets a tolerance based on the reliability, and a determination unit determines the area of the detected subject as a focus adjustment area if a difference between the predicted and detected positions is within the tolerance. The prediction unit predicts a position of an imaging plane of the subject in the focus adjustment area at a future time point.

Abstract: An image processing apparatus that is capable of improving subject detection accuracy with respect to image signals is disclosed. The image processing apparatus applies subject detection processing to an image by using a learning model generated based on machine learning. The image processing apparatus selects the learning model from a plurality of learning models stored in advance, in accordance with characteristics of the image to which the subject detection processing is to be applied.

Abstract: One aspect of the present invention provides an image processing apparatus capable of tracking an image region to be tracked with high accuracy. A distance distribution generation unit generates distance information indicating a distance of each of regions in first image data. An object likelihood distribution generation unit generates a likelihood distribution of an object in the first image data based on information indicating a position specified as the object in the first image data, the distance information, and reliability of the distance information. A feature amount extraction unit calculates a feature amount to be used to detect the object from second image data based on the likelihood distribution.

Abstract: An image forming device includes an image forming unit that forms an image on a recording medium in response to an input of image data representing the image, a reading unit that reads a first image formed by the image forming device, and a second image formed by another image forming device to respectively generate a first read image and a second read image, the first image and the second image being formed based on identical image data, a discrimination unit that discriminates the first read image and the second read image from each other, and a color correction unit that performs, on the image formed by the image forming unit, a color correction that cancels out a difference in color between the first read image and the second read image.

Abstract: A reading method guidance apparatus includes a receiving unit, an acquisition unit, and a guidance unit. The receiving unit receives a document size that is a size of a document as a reading target. The acquisition unit acquires an image of at least a partial area in the document. The guidance unit provides an operator with guidance about a reading procedure when the document is read by a first reading apparatus in plural batches, using a feature amount obtained from the acquired image, the received document size, and a readable size that is a size of an area readable by the first reading apparatus.

Abstract: A document size detecting apparatus includes a first acquisition unit, a second acquisition unit, and a detector. The first acquisition unit acquires a first image that is an image of an entire document as a reading target. The second acquisition unit acquires a second image that is an image of a part of the document read by a first reading apparatus. The detector detects a size of the document using a result of a matching process between the first image and the second image and a read size that is a size of the second image read by the first reading apparatus.

Abstract: The subject tracking apparatus comprises: a first registering unit configured to register a partial area as a template indicative of a subject in one image of supplied images; a first matching unit configured to estimate a subject area by collating a partial area in newly supplied images with the template registered by the first registering unit; a second registering unit configured to register a histogram generated based on a pixel value of a partial area indicative of the subject in one image of supplied images; a second matching unit configured to estimate a subject area by collating a histogram of a partial area in newly supplied images with the histogram registered by the second registering unit; and a tracking area determination unit configured to determine a tracking area based on estimation results by the first matching unit and the second matching unit.

Abstract: In an object tracking device that obtains image data, detects an object, and tracks a target object, a matching unit collates image data of a characteristic model that represents a tracking object, which is a tracking target, with input image data, and outputs a candidate region of the tracking object. An object region determination unit determines an object region from the candidate region that is output by the matching unit. A depth map calculation unit calculates depth information relating to the input image. An object depth setting unit obtains the object region that has been determined by the object region determination unit in the past and the depth information that has been calculated by the depth map calculation unit, and sets a predetermined depth range where the object can exist.

Abstract: An image capture apparatus functions as an object tracking apparatus for tracking an object included in provided images, registers a partial image indicating an object as a template, and performs template matching for estimating a region by using the template and histogram matching for registering a histogram of a partial image indicating the object and estimating a region by using the histogram. In a case where a distance between the estimation region based on the histogram matching and the estimation region based on the template matching is within a predetermined range, the estimation region based on the template matching is employed as an object region, and in a case where the distance between the estimation region based on the histogram matching and the estimation region based on the template matching is not within the predetermined range, the estimation region based on the histogram matching is employed as the object region.