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US 12,614,070 B2Granted
Object re-identification using pose part based models
AssigneeIntel Corporation
InventorsJianguo Li, Shuyuan Li, Hanlin Tang
Life of this patent
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Abstract
An example apparatus for re-identifying objects includes an image receiver to receive a first image and a second image of an object with an identity. The apparatus also includes a fused model generator to fuse a global representation of the object with local representations of pose parts of the object to generate a fused representation of the object based on the first image. The apparatus further includes an object re-identifier to re-identify the object with the identity in the second image based on the fused representation.
Claims22
An apparatus comprising:
- interface circuitry;
- machine-readable instructions;
- and
- at least one processor circuit to be programmed by the machine-readable instructions to:
- generate one or more local representations of pose parts of an object based on a first image of the object and a feature map associated with a global representation of the object, the pose parts associated with a skeleton structure of the object in a pose in the first image, each local representation including local part features of the object associated with a respective pose part, the first image captured by a first camera;
- aggregate the one or more local representations of the pose parts using a weighted summation of the local part features to generate aggregated local features;
- generate a fused representation of the object based on the aggregated local features and the global representation of the object;
- and
- re-identify the object in a second image based on the fused representation, the second image captured using a second camera different than the first camera.
6 more elements
A method comprising:
- globally modeling, by at least one processor circuit programmed by at least one instruction, an object based on a first input object image to generate a global representation of the object, the global representation including a feature map, the first input object image captured by a first camera;
- estimating, by one or more of the at least one processor circuit, pose keypoints of the object in the first input object image;
- generating, by one or more of the at least one processor circuit, a skeleton structure of the object based on the pose keypoints;
- modeling, by one or more of the at least one processor circuit, local parts of the object in the first input object image based on the feature map and the skeleton structure to generate one or more local representations of pose parts of the object, the pose parts associated with the skeleton structure of the object in a pose in the first input object image, each local representation including local part features of the object associated with a respective pose part;
- aggregating, by one or more of the at least one processor circuit, the one or more local representations of the pose parts using a weighted summation of the local part features to generate aggregated local features;
- generating, by one or more of the at least one processor circuit, a fused representation of the object based on the aggregated local features and the global representation of the object;
- and
- re-identifying, by one or more of the at least one processor circuit, the object in a second input object image based on the fused representation, the second input object image captured using a second camera different than the first camera.
5 more elements
A system comprising:
- means for generating one or more local representations of pose parts of an object based on a first image of the object and a feature map associated with a global representation of the object, the pose parts associated with a skeleton structure of the object in a pose in the first image, each local representation including local part features of the object associated with a respective pose part, the first image captured by a first camera;
- means for fusing to generate a fused representation of the object, the means for fusing to:
- aggregate the one or more local representations of the pose parts using a weighted summation of the local part features to generate aggregated local features;
- and
- generate a fused representation of the object based on the aggregated local features and the global representation of the object;
- and
- means for re-identifying the object in a second image based on the fused representation, the second image captured using a second camera different than the first camera.
4 more elements
Dependencies are inferred from the claim text.