Abstract: In a program generation apparatus, a processing unit selects a first program from among a plurality of image processing programs each generated by combining a plurality of partial programs; generates a second program by changing a part of the partial programs included in the first program; performs image processing on an input image, using the second program; determines whether to pass the second program to the next generation, based on a comparison between one or more intermediate output images that are output halfway through the image processing and a first target image; and replaces one of the image processing programs with the second program when the second program is determined to be passed to the next generation.

Abstract: In a preparation stage, an abnormality detection device detects a first characteristic amount from each first frame contained in video data and stores the first characteristic amount in a storage unit. In an abnormality detection stage, the abnormality detection device detects a second characteristic amount from each second frame contained in video data obtained by imaging a work operation of the robot and stores the first characteristic amount in the storage unit. The abnormality detection device compares the second characteristic mount of the second frame and the first characteristic amount of each of the first frames and specifies the first characteristic amount that is the closest to the second characteristic amount. The abnormality detection device determines whether the work operation of the robot in the abnormality detection stage is abnormal on the basis of the specified first characteristic amount and the second characteristic amount.

Abstract: An information processing apparatus includes a memory that stores information indicating a first individual and a processing result that is output by each node of the first individual in a process of executing image processing based on the first individual; and a processor coupled to the memory and configured to: generate a second individual based on the first individual; specify subtrees that have the same content and include terminating nodes between a tree structure indicating the second individual and a tree structure indicating the first individual; and set a processing result corresponding to a head node of the subtree included in the first individual, which is stored in the memory, as a result of executing image processing based on the subtree included in the second individual when adaptability of the second individual is calculated based on a result of executing image processing based on the second individual.

Abstract: A setting unit sets a selection probability for each of a plurality of parameter values selectively configurable in a parameter-variable program amongst a plurality of partial programs, based on a relationship between the parameter values and an amount of characteristic obtained from at least an input image included in learning data. When having selected the parameter-variable program as a partial program to be newly assigned to a target position for a mutation in order to evolve an individual by introducing the mutation, a selection processing unit selects, amongst the parameter values, one parameter value according to the selection probabilities respectively associated with the parameter values, and incorporates the parameter-variable program with the selected parameter value set therein into the individual.

Abstract: An information processing apparatus includes a processor and a memory. The memory stores three-dimensional data describing a real device including an object, a source of an acting factor that acts on the object and causes a detectable change at the object, and a detector that detects the change in a specified detection range. The processor produces a virtual device that represents the real device in a virtual space, based on the three-dimensional data in the memory. With this virtual device, the processor simulates the change caused by the acting factor, and calculates a region of the object in which the simulated change satisfies a specified condition.

Abstract: An information processing apparatus includes: a memory configured to store an image processing program having a tree structure in which a partial program is incorporated in each of a plurality of nodes; and a processor configured to performs, based on the image processing program, operations of; calculating a feature amount based on a processing result in each intermediate node excluding a terminal node among the plurality of nodes when executing image processing on a captured image which is captured by an imaging device; and calculating a performance evaluation value of the image processing program based on a variation amount of the feature amount in accordance with elapse of time.

Abstract: An input picture generation unit generates a virtually photographed picture including an object of interest photographed in a virtual space and outputs the virtually photographed picture as an input picture for use in generating an image processing program through learning. A target picture generation unit receives selection of feature data corresponding to a feature portion of the object of interest, from among geometric data representing a three-dimensional shape of the object of interest. The target picture generation unit calculates a projected position of the feature portion in the input picture, based on the feature data, and generates a target picture corresponding to the input picture, based on the calculated projected position.

Abstract: An apparatus stores a plurality of partial programs, which are constituent elements of an image recognizing program that detects a position of a template image on an input image. The apparatus creates a plurality of individual programs each being a combination of at least two of the plurality of partial programs, and calculates a similarity map that associates similarity with the template image with each pixel of the input image by using each of the plurality of individual programs. The apparatus calculates fitness for each of the plurality of individual programs, based on a distribution of the similarity map, selects an individual program for which the fitness is equal to or greater than a prescribed threshold, from among the plurality of individual programs, and outputs the selected individual program as the image recognizing program.

Abstract: There is provided a program generating apparatus including a generating unit and a genetic processing unit. The generating unit is configured to generate tree structures each representing an image classification program. Each of the tree structures has a first level group and a second level group. Elements of nodes in the first level group are selected from amongst image filters each used to apply preprocessing to an input image. An element of a node in the second level group is selected from amongst setting programs each used to set a different value as a control parameter for generating a classifier based on information obtained by execution of the elements selected for the nodes in the first level group. The genetic processing unit is configured to output, using genetic programming, a tree structure with a fitness score exceeding a predetermined threshold based on the tree structures.

Abstract: In a program generation apparatus, an operating unit repeatedly performs setting process of calculating the increasing rate of the maximum fitness level among the fitness levels of individuals included in a population, setting a setting value indicating the number of child individuals to be generated to a first value if the increasing rate is higher than or equal to a first threshold and setting the setting value to a second value greater than the first value if the increasing rate is lower than the first threshold, an evolution process of generating as many child individuals as specified by the setting value, based on a parent individual selected from the individuals included in the population, and a survival selection process of selecting an individual with the highest fitness level from the parent and child individuals and replacing one of the individuals in the population with the selected individual.

Abstract: An abnormal detection apparatus including an imaging unit configured to image generate a first and second image frames included in a first image frame group; a pseudo work generation unit configured to generate the first and a third image frames, the third and the second image frames, or the third and a fourth image frames, included in a second image frame group, respectively, with respect to the first and second image frames included in the first image frame group; a normal space generation unit configured to generate a normal space data based on the first and second image frames included in the first image frame group, and the first and third image frames, the third and second image frames, or the third and fourth image frames, included in the second image frame group; and a comparison unit configured to detect abnormality based on the normal space data.

Abstract: In a program generation apparatus, a processing unit selects a first program from among a plurality of image processing programs each generated by combining a plurality of partial programs; generates a second program by changing a part of the partial programs included in the first program; performs image processing on an input image, using the second program; determines whether to pass the second program to the next generation, based on a comparison between one or more intermediate output images that are output halfway through the image processing and a first target image; and replaces one of the image processing programs with the second program when the second program is determined to be passed to the next generation.

Abstract: In order to produce an image processing filter by utilizing genetic programming, a taught parameter acquiring unit acquires a taught parameter indicating a feature shape in an input image before processing. A data processing unit creates an output image by processing the input image with an image processing filter, and subsequently a feature extracting unit extracts a detected parameter indicating a feature shape in the output image. An automatic configuring unit evaluates the image processing filter by calculating cosine similarity between the taught parameter and the detected parameter.

Abstract: In a preparation stage, an abnormality detection device detects a first characteristic amount from each first frame contained in video data and stores the first characteristic amount in a storage unit. In an abnormality detection stage, the abnormality detection device detects a second characteristic amount from each second frame contained in video data obtained by imaging a work operation of the robot and stores the first characteristic amount in the storage unit. The abnormality detection device compares the second characteristic mount of the second frame and the first characteristic amount of each of the first frames and specifies the first characteristic amount that is the closest to the second characteristic amount. The abnormality detection device determines whether the work operation of the robot in the abnormality detection stage is abnormal on the basis of the specified first characteristic amount and the second characteristic amount.

Abstract: An image processing apparatus is disclosed. A processor performs a process that arranges multiple image filters in a tree structure and acquires features of multiple input images captured in different environments. A storage part stores a filter table that maintains information concerning the multiple image filters. In the process, an image filter having a different type for each of layers, in which multiple image processes are hierarchized, is selected from the filter table. A population, which includes the multiple image filters in the tree structure, is generated.

Abstract: A setting unit sets a selection probability for each of a plurality of parameter values selectively configurable in a parameter-variable program amongst a plurality of partial programs, based on a relationship between the parameter values and an amount of characteristic obtained from at least an input image included in learning data. When having selected the parameter-variable program as a partial program to be newly assigned to a target position for a mutation in order to evolve an individual by introducing the mutation, a selection processing unit selects, amongst the parameter values, one parameter value according to the selection probabilities respectively associated with the parameter values, and incorporates the parameter-variable program with the selected parameter value set therein into the individual.

Abstract: Each time evolution processing is performed, an information recording unit records increase-decrease information indicating a type of partial program changed in number between pre- and post-evolution individuals and difference between fitness levels calculated from the pre- and post-evolution individuals in a storage unit. A probability setting unit determines, per partial program, a contribution level indicating how much a partial program contributes to increasing a fitness level, based on the information stored in the storage unit within a predetermined period and sets a selection probability per partial program in such a manner that a partial program having a higher contribution level is given a higher selection probability. When the evolution processing is performed, a generation processing unit selects a partial program to be included in the post-evolution individual in mutation processing according to the set selection probabilities.

Abstract: An apparatus stores a plurality of partial programs, which are constituent elements of an image recognizing program that detects a position of a template image on an input image. The apparatus creates a plurality of individual programs each being a combination of at least two of the plurality of partial programs, and calculates a similarity map that associates similarity with the template image with each pixel of the input image by using each of the plurality of individual programs. The apparatus calculates fitness for each of the plurality of individual programs, based on a distribution of the similarity map, selects an individual program for which the fitness is equal to or greater than a prescribed threshold, from among the plurality of individual programs, and outputs the selected individual program as the image recognizing program.

Abstract: A processor divides each of a plurality of images in which an imaging target is captured under a plurality of different illumination conditions into a plurality of areas, to generate a plurality of divided areas. According to luminance information of a plurality of divided images corresponding to one area among the plurality of areas, the processor selects one divided image among the plurality of divided images corresponding to the one area. Further, the processor combines the one divided image with divided images corresponding to areas other than the one area, to generate an image corresponding to the plurality of areas.

Abstract: An information processing apparatus includes a processor and a memory. The memory stores three-dimensional data describing a real device including an object, a source of an acting factor that acts on the object and causes a detectable change at the object, and a detector that detects the change in a specified detection range. The processor produces a virtual device that represents the real device in a virtual space, based on the three-dimensional data in the memory. With this virtual device, the processor simulates the change caused by the acting factor, and calculates a region of the object in which the simulated change satisfies a specified condition.