Object recognition device, method, and computer-readable medium
AssigneeNEC Corporation
InventorsAzusa Sawada, Soma Shiraishi, Takashi Shibata
Life of this patent
Estimating the term…
Abstract
The learning device includes a metric space learning unit and a case example storage unit. The metric space learning unit learns a metric space including feature vectors extracted from attributed image data, for each combination of different attributes, using the attributed image data to which attribute information is assigned. The case example storage unit computes the feature vector from the image data for case example to store the computed feature vector as a case example associated with the metric space, and stores additional information associated with the case example.
Claims12
An inference device comprising:
- a memory configured to store instructions;
- and
- one or more processors configured to execute the instructions to:
- store a feature vector of image data for case example in association with a metric space learned for each combination of different attributes, and store additional information associated with the case example by a learning method;
- wherein the learning method comprises:
- learning a metric space including feature vectors extracted from attributed image data, for each combination of different attributes, using the attributed image data to which attribute information is assigned;
- and
- computing the feature vector from the image data for case example to store the computed feature vector as a case example associated with the metric space, and storing additional information associated with the case example;
- identify image data for inference based on the feature vector extracted from the image data for inference and the case example associated with the metric space;
- and
- generate, using the additional information associated with the case example used for identification, an identification result.
An inference method comprising:
- acquiring a metric space from a case example storage which stores a feature vector of image data for case example in association with a metric space learned for each combination of different attributes, and which stores additional information associated with the case example, the case example storage being created by a learning method;
- wherein the learning method comprises:
- learning a metric space including feature vectors extracted from attributed image data, for each combination of different attributes, using the attributed image data to which attribute information is assigned;
- and
- computing the feature vector from the image data for case example to store the computed feature vector as a case example associated with the metric space, and storing additional information associated with the case example;
- identifying image data for inference based on a feature vector extracted from the image data for inference and the case example associated with the metric space;
- and
- generating, using the additional information associated with the case example used for identification, an identification result.
A non-transitory computer-readable recording medium recording a program causing a computer to execute processing of:
- acquiring a metric space from a case example storage unit-which stores a feature vector of image data for case example in association with a metric space learned for each combination of different attributes, and which stores additional information associated with the case example, the case example storage being created by a learning method;
- wherein the learning method comprises:
- learning a metric space including feature vectors extracted from attributed image data, for each combination of different attributes, using the attributed image data to which attribute information is assigned;
- and
- computing the feature vector from the image data for case example to store the computed feature vector as a case example associated with the metric space, and storing additional information associated with the case example;
- identifying image data for inference based on a feature vector extracted from the image data for inference and the case example associated with the metric space;
- and
- generating, using the additional information associated with the case example used for identification, an identification result.
Dependencies are inferred from the claim text.