Method for detecting object
First Claim
1. A method of detecting an object through a retrieve of an image representing an object matched to an object represented by a query image from an image database that includes a plurality of reference images and is created by extracting a plurality of reference feature vectors from each reference image that represents an object, each of the reference feature vectors representing a feature of one of local areas in each reference image, and by storing the reference feature vectors in such a manner that each of the reference feature vectors is associated with the corresponding reference image and with an object ID that identifies the object represented by each reference image, the method comprising the steps of:
- extracting a plurality of vectors from the query image as query feature vectors, each of the query feature vectors representing a feature of one of local areas in the query image;
comparing each query feature vector with each reference feature vector, and calculating a similarity score that is determined to have a greater value in case where the query feature vector and the reference feature vector are closer, in case where a local area from which the query feature vector is extracted is greater, and in case where a local area from which the reference feature vector is extracted is greater;
determining a reference feature vector which provides the highest similarity score as a similar vector for each query feature vector; and
obtaining resulting scores through a predetermined calculation procedure according to the respective object IDs, each object ID being associated with the similar vector, and determining, as a detection result, at least one object that is specified by an object ID giving the highest resulting score,wherein each resulting score is calculated according to the following equation ;
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Abstract
An object detection method that is provided with a step for extracting a plurality of reference feature vectors related to a local area from an image representing an object, and extracting a plurality of query feature vectors related to the local area from a search query image; a step for matching each query feature vector against each reference feature vector, and calculating a similarity score having a value that is higher the closer the distance between both vectors, the larger the local area for which the query feature vector has been extracted, and the larger the local area for which a matching reference feature vector has been extracted; a step for determining a reference feature vector for which a similarity score is highest as the similar vector for each query feature vector; and a step for acquiring a final score by object associated with the similar vectors, and setting the object returning the highest score as the detection result; and wherein the score is calculated by dividing a sum of the similarity score for each similar vector by the number of feature vectors that have matched the object.
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Citations
8 Claims
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1. A method of detecting an object through a retrieve of an image representing an object matched to an object represented by a query image from an image database that includes a plurality of reference images and is created by extracting a plurality of reference feature vectors from each reference image that represents an object, each of the reference feature vectors representing a feature of one of local areas in each reference image, and by storing the reference feature vectors in such a manner that each of the reference feature vectors is associated with the corresponding reference image and with an object ID that identifies the object represented by each reference image, the method comprising the steps of:
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extracting a plurality of vectors from the query image as query feature vectors, each of the query feature vectors representing a feature of one of local areas in the query image; comparing each query feature vector with each reference feature vector, and calculating a similarity score that is determined to have a greater value in case where the query feature vector and the reference feature vector are closer, in case where a local area from which the query feature vector is extracted is greater, and in case where a local area from which the reference feature vector is extracted is greater; determining a reference feature vector which provides the highest similarity score as a similar vector for each query feature vector; and obtaining resulting scores through a predetermined calculation procedure according to the respective object IDs, each object ID being associated with the similar vector, and determining, as a detection result, at least one object that is specified by an object ID giving the highest resulting score, wherein each resulting score is calculated according to the following equation ; - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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Specification