Abstract: It is an object of the present invention to provide a user interface which facilitates confirmation of an area in an image and associated data corresponding to the area without requiring user's complicated operations. To achieve the object, an information processing apparatus comprises: an obtaining unit configured to obtain a first image including a plurality of objects, and information related to respective positions of the plurality of objects in the first image; and a determining unit configured to determine a position in case of shifting and displaying a second image indicating the plurality of objects with respect to the first image, based on the obtained positions of the plurality of objects.

Abstract: An apparatus includes an acquisition unit that acquires a first image based on a first parameter, and a second image based on a second parameter, a segmentation unit that segments each of the first and second images into a plurality of segments, an acquisition unit that acquires feature quantities from each of the plurality of segments formed by segmenting the first and second images, respectively, a calculation unit that calculates a reliability of each of the plurality of segments of the first image based on the feature quantities acquired from the first image, a classification unit that classifies the plurality of segments of the first image into a first field having a relatively high reliability and a second field having a relatively low reliability, and a determination unit that determines categories for the first and second fields based on the feature quantities acquired from the first and second images.

Abstract: A method for information processing includes a learning process to generate a tree structured dictionary based on a plurality of patterns including a target object to be recognized. The method includes selecting a plurality of points from an input pattern based on a distribution of a probability that the target object to be recognized is present in the input pattern at each node of a tree structure generated in the learning process, and classifying the input pattern into a branch based on a value of a predetermined function that corresponds to values of the input pattern at selected plurality of points.

Abstract: An image recognition apparatus is provided which comprises a first extracting means for extracting, from every registration image previously registered, a set of registration partial images of a predetermined size, and a second extracting means for extracting, from an input new image, a set of new partial images of a predetermined size. The apparatus further comprises a discriminating means for discriminating an attribute of the new partial image based on a rule formed by dividing the set of the registration partial images extracted by the first extracting means, and a collecting means for deriving a final recognition result of the new image by collecting discrimination results by the discriminating means at the time when the new partial images as elements of the set of the new partial images are input.

Abstract: A Deep Neural Network (DNN) having a plurality of recognition tasks with different scales makes it possible to perform recognition processing in a network where identification layers are branched from one intermediate layer. An image recognition apparatus for recognizing a target includes a first acquisition unit configured to acquire from an input image a first intermediate feature amount for performing first identification, a first identification unit configured to perform the first identification based on the first intermediate feature amount, a second acquisition unit configured to acquire from the first intermediate feature amount a second intermediate feature amount for performing second identification having a larger scale than the first identification, and a second identification unit configured to perform the second identification based on the second intermediate feature amount.

Abstract: An information processing apparatus includes a reception unit configured to receive an input specifying a position of a detection target included in an image, an acquisition unit configured to acquire a storage amount of training data including a pair of information indicating the image and information indicating the position specified by the input, a training unit configured to train a training model to detect the detection target from the image based on the stored training data, and a display control unit configured to control a display unit to display the storage amount, and a reference amount of the training data set as an amount of the training data necessary for the training unit to train the training model, in a comparable way.

Abstract: An information processing apparatus performs estimation processing on supervised data, and stores a relationship between teacher information and an estimation result. When unsupervised data is input, the information processing apparatus searches for supervised data high in degree of similarity in estimation result to unsupervised data, and generates teacher information from an estimation result of unsupervised data based on a relationship between teacher information and an estimation result about the detected supervised data.

Abstract: An apparatus comprising: an obtaining unit configured to obtain target data as a result of discrimination of each portion of input data performed by a discriminator having learned in advance by using existing labeled data; a setting unit configured to set each portion of the target data, which is effective for additional learning of the discriminator, as local data; a determining unit configured to determine not less than one partial region of the target data, which accepts labeling by a user, based on a distribution of the set local data in the target data; and a display control unit configured to cause a display unit to display the determined not less than one partial region.

Abstract: An image processing apparatus includes: an acquisition unit configured to acquire a plurality of images each capturing an identical target and having a different attribute; a derivation unit configured to derive features from the plurality of images, using a first neural network; an integration unit configured to integrate the features derived from the plurality of images; and a generation unit configured to generate a higher quality image than the plurality of images from the feature integrated by the integration unit, using a second neural network.

Abstract: An apparatus according to the present disclosure acquires a display condition for displaying at least a part of target data as a display image on a display unit, determines, in a case where the display image is changed, whether to store the display condition according to a changed display image in a storage unit, based on an index relating to the change of the display image, and stores, in a case where the display condition is determined to be stored, the display condition according to the changed display image in the storage unit.

Abstract: In the present disclosure, an image parameter of an input image is changed, features is extracted from each of a plurality of generated images, a category of each region is determined based on the features in each image, and the results are integrated.

Abstract: A learning apparatus includes an acquisition unit, a creation unit, and a first learning unit. The acquisition unit acquires a plurality of leaning data sets including a plurality of images imaged by a plurality of imaging devices, and sensor information of the imaging devices when the plurality of respective images is imaged. The creation unit creates, from the plurality of the plurality of learning data sets, a plurality of subsets, wherein each of the plurality of subsets has a different combination of the plurality of images and the sensor information. The first learning unit learns a plurality of first classifiers respectively corresponding to the plurality of subsets based on the plurality of respective subsets.

Abstract: In order to reduce limitations on an arrangement of a posture visualization system as a whole, a posture recognition unit recognizes, based on image data of a real space captured by an image capture unit from a predetermined viewpoint, a posture of an object in the image data of the real space. A posture visualization viewpoint setting unit sets a viewpoint different from the predetermined viewpoint. A posture visualization unit visualizes a mirror image of the posture of the object viewed from the viewpoint set by the posture visualization viewpoint setting unit based on the posture recognized by the posture recognition unit. A space display unit displays the mirror image of the posture of the object generated by the posture visualization unit and a mirror image of the real space at once.

Abstract: An object detection apparatus first sets a first partial region having a preset size and a second partial region in a given point (pixel) in an input image. In addition, the object detection apparatus calculates a first information amount in the second partial region, and sets a third partial region based on the size of the first information amount. Furthermore, the object detection apparatus calculates a score based on a salience degree that is based on a difference in statistical feature amount distribution between the first partial region and the second partial region, and based on an information amount of feature amount in the third partial region. Lastly, the object detection apparatus detects a main object by calculating scores on the respective points in the image and applying a predetermined statistical process to the scores.

Abstract: An image processing apparatus includes detecting means for detecting a first detected region and a second detected region from an input image, on the basis of a first detection criterion and a second detection criterion, respectively; image setting means for setting, as a target image subjected to correction, an image including the first detected region, and setting, as a reference image that is referred to in the correction, an image including the second detected region; accepting means for accepting, from a user, designation of a region in the target image and a correction instruction for the designated region; correction region setting means for identifying, in the reference image, a region corresponding to the designated region, and for setting a to-be-corrected region on the basis of the identified region and the second detected region; and correcting means for correcting the first detected region in the target image on the basis of the to-be-corrected region set in the reference image.

Abstract: Some embodiments are directed to, by a simple operation, appropriately displaying an image to which attention is paid. An information processing apparatus according to some embodiments is an information processing apparatus for performing display for measuring a width of a region in an image of an inspection target object, the information processing apparatus including an acquisition unit configured to acquire a bending position where a bend of a line approximating the region from the image satisfies a predetermined condition, and a display control unit configured to display, in an aligned manner in a predetermined direction, a plurality of partial images obtained by dividing the image based on the bending position.

Abstract: An image processing system comprises: an image recognizing unit which performs image recognition to an image; a rule setting unit which sets a sorting rule to be used in case of transmitting the image recognized by the image recognizing unit to an external web service; and a transmitting unit which transmits, according to the sorting rule having a condition conforming to the image among the sorting rules set by the rule setting unit, information concerning the image to the corresponding external web service, thereby enabling to cooperate a still image/moving image sharing service and various web services with others.

Abstract: To enable a response to an urgent call-out caused by a failure occurrence, the degree of an occurrence of a failure in each of a plurality of apparatuses installed at different locations is predicted and a visit plan of each of a plurality of servicemen is created based on a prediction result.

Abstract: An apparatus for monitoring an object in a video received from at least one camera, comprises a storage unit storing a plurality of pieces of rule information each defining a condition of an object and a movement of the object to be observed in the condition, an input unit inputting information for identifying a monitored object and information representing a condition of the object, an acquiring unit acquiring rule information defining a movement to be observed for the object by referring to the storage unit based on the information representing the condition of the object, which is input by the input unit; and a monitoring unit determining whether the object in the video exhibits the movement to be observed, which is represented by the rule information acquired by the acquiring unit, and output a result of the determination.

Abstract: A pattern recognition apparatus extracts a feature amount of each of a plurality of pixels included in an input image, and calculates, for each of the plurality of pixels, a degree of matching between the feature amount of the pixel and the feature amount of each of one or more pixels included in a peripheral area of the pixel. Then, the pattern recognition apparatus estimates a position of each of a plurality of objects to be recognized by voting for one or more of the plurality of objects to be recognized from each of the plurality of pixels based on the extracted feature amount and the calculated degree of matching.