Abstract:
Provided is an object detection device for efficiently and simply selecting an image for creating instructor data on the basis of the number of detected objects. The object detection device is provided with: a detection unit for detecting an object from each of a plurality of input images using a dictionary; an acceptance unit for displaying, on a display device, a graph indicating the relationship between the input images and the number of subregions in which the objects are detected, and displaying, on the display device, in order to create instructor data, one input image among the plurality of input images in accordance with a position on the graph accepted by operation of an input device; a generation unit for generating the instructor data from the input image; and a learning unit for learning a dictionary from the instructor data.
Abstract:
A POS-terminal device includes: a housing that is provided with a product-reading device including an imaging unit configured to capture a product to generate an image; a product-input unit configured to input the product, the product-input unit including a product-reading frame configured to define an outer edge of an imaging area of the imaging unit; and a reflector configured to reflect a subject image of the product passed over the imaging area, outside the housing.
Abstract:
A model training apparatus acquires a first training data set including a first training image representing a scene in a first environment and first class information indicating a class of each of a plurality of image regions included in the first training image. The model training apparatus inputs the first training image to an image conversion model to acquire an output image representing a scene in a second environment, inputs the output image to a discrimination model to acquire discrimination data, and trains the image conversion model using the discrimination data and the first class information. The discrimination data indicates, for each of a plurality of partial regions included in an image input to the discrimination model, whether or not the partial region is a fake image region, and indicates a class of the partial region when the partial region is not a fake image.
Abstract:
Provided is an object detection device for efficiently and simply selecting an image for creating instructor data on the basis of the number of detected objects. The object detection device is provided with: a detection unit for detecting an object from each of a plurality of input images using a dictionary; an acceptance unit for displaying, on a display device, a graph indicating the relationship between the input images and the number of subregions in which the objects are detected, and displaying, on the display device, in order to create instructor data, one input image among the plurality of input images in accordance with a position on the graph accepted by operation of an input device; a generation unit for generating the instructor data from the input image; and a learning unit for learning a dictionary from the instructor data.
Abstract:
The information processing device performs distillation learning of a student model using unknown data which a teacher model has not learned. The label distribution determination unit outputs an arbitrary label for the unknown data. The data generation unit outputs new generated data using an arbitrary label and unknown data as inputs. The distillation learning part performs distillation learning of the student model using the teacher model and using the generated data as an input.
Abstract:
In an object detection device, a plurality of object detection units output a score indicating probability that a predetermined object exists, for each partial region set to image data inputted. The weight computation unit computes weights for merging the scores outputted by the plurality of object detection units, using weight calculation parameters, based on the image data. The merging unit merges the scores outputted by the plurality of object detection units, for each partial region, with the weights computed by the weight computation unit. The target model object detection unit configured to output a score indicating probability that the predetermined object exists, for each partial region set to the image data. The first loss computation unit computes a first loss indicating a difference of the score of the target model object detection unit from a ground truth label of the image data and the score merged by the merging unit. The first parameter correction unit corrects parameters of the target model object detection unit to reduce the first loss.
Abstract:
To improve pose estimation accuracy, a pose estimation apparatus according to the present invention extracts a person area from an image, and generates person area image information, based on an image of the extracted person area. The pose estimation apparatus according to the present invention further extracts a joint point of a person from the image, and generates joint point information, based on the extracted joint point. Then, the pose estimation apparatus according to the present invention generates feature value information, based on both of the person area image information and the joint point information. Then, the pose estimation apparatus according to the present invention estimates a pose of a person included in the image, based on an estimation model in which the feature value information is an input, and pose estimation result is an output.
Abstract:
A three-dimensional space generating unit 81 generates a three-dimensional space modeling a three-dimensional model with associated attributes and a first background in a virtual space. A two-dimensional object drawing unit 82 draws a two-dimensional object by projecting the three-dimensional model in the three-dimensional space onto a two-dimensional plane. A label generating unit 83 generates a label from the attributes associated with the three-dimensional model from which the two-dimensional object is projected. A background synthesizing unit 84 generates a two-dimensional image by synthesizing the two-dimensional object and a second background. A training data generating unit 85 generates training data that associates the two-dimensional image in which the second background and the two-dimensional object are synthesized with the generated label.
Abstract:
Provided is a target member for accurately guiding a moving body to a target site. A target member 10 is used when performing control for guiding a moving body 20 to a target site, and the target member 10 is formed by using two or more different feature members 11, 12 that are set such that a shape of a target member image 44 that corresponds to the target member 10 captured by an image capturing unit 21 (an image capturing apparatus) that is mounted in the moving body 20 changes according to a measurement distance that indicates a distance between the target member 10 and the moving body 20.
Abstract:
The present invention is a two-wheel vehicle riding person number determination system including an imaging means configured to image a two-wheel vehicle that is installed in a predetermined position and travels on a road, and a two-wheel vehicle riding person number determining means configured to process an image of the imaging means, extract a contour shape of an upper position of the two-wheel vehicle that travels on the road, detect humped shapes corresponding to heads of persons who ride on the two-wheel vehicle from the contour shape of the upper position of the two-wheel vehicle, and determine, on the basis of the humped shapes, whether or not the number of the persons who ride on the two-wheel vehicle is at least two persons or more.