A local visual feature selection method and device
A visual feature and feature selection technology, applied in the computer field, to achieve the effect of reliable retrieval results
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Embodiment 1
[0055] figure 1 is a schematic flow chart of a local visual feature selection method provided in Embodiment 1 of the present invention, as shown in figure 1 As shown, the method includes the following steps:
[0056] S101: Detect and acquire multiple local visual features in the target image, and obtain the own attributes of each local visual feature.
[0057] Specifically, the local visual feature detection method is used to detect the local visual features in the target image, form a complete set of local visual feature descriptors, and obtain the own attributes of each local visual feature.
[0058] Wherein, the local visual feature detection method may be any detection method suitable for local visual features of an image, such as a local visual feature detection method in Scale Invariant Feature Transform (SIFT for short).
[0059] Wherein, the own attributes of the local visual features may be the attributes contained in the local visual features detected by the above ...
Embodiment 2
[0087] image 3 is a schematic flow chart of a local visual feature selection method provided in Embodiment 2 of the present invention, as shown in image 3 As shown, the method includes the following steps:
[0088] S301: Detect and acquire multiple local visual features in the target image, and obtain the own attributes of each local visual feature.
[0089] This step S301 is the same as the step S101 in Embodiment 1, and will not be repeated here.
[0090] S302: Obtain depth information of all the local visual features, and obtain depth attributes of the local visual features through a normalization method.
[0091] Optionally, for a local visual feature, the acquired depth information may be a depth value of the local visual feature from the camera, or a disparity value of the local visual feature.
[0092] The local visual features of the target image are all concentrated. In order to obtain the depth value of each local visual feature from the camera, the method of ob...
Embodiment 3
[0113] Figure 4 It is a schematic flowchart of a local visual feature selection method provided by Embodiment 3 of the present invention. The difference between this embodiment and Embodiment 2 is that some depth information acquisition methods can only obtain a part of the complete set of local visual features in the target image. Depth information of visual features. In this case, this embodiment provides another possible numerical calculation method for local visual features.
[0114] Specifically, such as Figure 4 As shown, the method includes the following steps:
[0115] S401: Detect and acquire multiple local visual features in the target image, and obtain the own attributes of each local visual feature.
[0116] This step S401 is the same as the step S101 in Embodiment 1, and will not be repeated here.
[0117] S402: Obtain depth information of some of the partial visual features, and obtain depth attributes of the partial visual features through a normalization m...
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