Methods and apparatuses for facilitating object recognition
AssigneeNokia Technologies Oy
InventorsJiangwei Li, Kongqiao Wang, Lei Xu
Life of this patent
Estimating the term…
Abstract
Methods and apparatuses are provided for facilitating object recognition. A method may include accessing data for a first object and data for a second object. The method may additionally include comparing the first and second objects based at least in part upon a reference set and training results generated based at least in part upon the reference set and training data. The method may further include determining whether the first object and the second object are the same object based at least in part upon the comparison. Corresponding apparatuses are also provided.
Claims18
A method comprising:
- accessing data for a first object and data for a second object;
- extracting a reference feature (Pjia) from each of the first object and the second object, wherein the reference feature (Pjia) is represented as:
- Pjia=SaT(Trji−ma)
- where Trji is training data comprising a discriminative subspace and Trji={Trj1, Trj2, . . . , Trji, . . . |j≦G} among G face classes,
- where ma is a reference mean, and Sais a reference manifold and SaT is a transformation matrix of Sa;
- comparing, by a processor, the first and second objects based at least in part upon the reference features from each of the first and second object, wherein the comparing comprises:
- mapping the extracted first and second reference features on the discriminative subspace to obtain a first merged feature and a second merged feature;
- determining a distance between the first and second merged features;
- and
- determining whether the first object and the second object are the same object comprises determining whether the first object and the second object are the same object based at least in part upon the determined distance;
- and
- determining, using a processor, whether the first object and the second object are the same object based at least in part upon the comparison.
An apparatus comprising at least one processor and at least one memory storing computer program code, wherein the at least one memory and stored computer program code are configured to, with the at least one processor, cause the apparatus to at least:
- access data for a first object and data for a second object;
- extract a reference feature (Pjia) from each of the first object and the second object, wherein the reference feature (Pjia) is represented as:
- Pjia=SaT(Trji−ma)
- where Trji is training data comprising a discriminative subspace and Trji={Trj1, Trj2, . . . , Trji, . . . |j≦G} among G face classes,
- where ma is a reference mean, and Sa is a reference manifold and SaT is a transformation matrix of Sa;
- compare the first and second objects based at least in part upon the reference features from each of the first and second object, wherein causing the apparatus to compare the first and second objects comprises causing the apparatus to:
- map the extracted first and second reference features on the discriminative subspace to obtain a first merged feature and a second merged feature;
- and
- determine a distance between the first and second merged features;
- and
- the at least one memory and stored computer program code are configured to, with the at least one processor, cause the apparatus to determine whether the first object and the second object are the same object by determining whether the first object and the second object are the same object based at least in part upon the determined distance;
- and
- determine whether the first object and the second object are the same object based at least in part upon the comparison.
A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program instructions stored therein, the computer-readable program instructions comprising program instructions configured to:
- access data for a first object and data for a second object;
- extract a reference feature (Pjia) from each of the first object and the second object, wherein the reference feature (Pjia) is represented as:
- Pjia=SaT(Trji−ma)
- where Trji is training data comprising a discriminative subspace and Trji={Trj1, Trj2, . . . , Trji, . . . |j≦G} among G face classes,
- where ma is a reference mean, and Sa is a reference manifold and SaT is a transformation matrix of Sa;
- compare the first and second objects based at least in part upon the reference features from each of the first and second object, wherein the program code instructions configured to compare the first and second objects comprises program code instructions to:
- map the extracted first and second reference features on the discriminative subspace to obtain a first merged feature and a second merged feature;
- determine a distance between the first and second merged features;
- and
- determine whether the first object and the second object are the same object comprises determining whether the first object and the second object are the same object based at least in part upon the determined distance;
- and
- determine whether the first object and the second object are the same object based at least in part upon the comparison.
Dependencies are inferred from the claim text.