JOINT-BASED ITEM RECOGNITION

摘要

For an input image of a person, a set of object proposals are generated in the form of bounding boxes. A pose detector identifies coordinates in the image corresponding to locations on the person's body, such as the waist, head, hands, and feet of the person. A convolutional neural network receives the portions of the input image defined by the bounding boxes and generates a feature vector for each image portion. The feature vectors are input to one or more support vector machine classifiers, which generate an output representing a probability of a match with an item. The distance between the bounding box and a joint associated with the item is used to modify the probability. The modified probabilities for the support vector machine are then compared with a threshold and each other to identify the item.

主权项

1. A system comprising:
a memory having instructions embodied thereon; and one or more processors configured by the instructions to perform operations comprising:
analyzing an image of a person to determine a set of joints of the person;generating a set of candidate bounding boxes, each bounding box of the set of candidate bounding boxes defining a portion of the image; andanalyzing the portion of the image defined by a bounding box of the set of candidate bounding boxes to identify an item of apparel, the identification being based on a distance between the bounding box and a joint of the set of joints.