MMSF works on the obtained regions of pre-segmentation step that are considered as nodes of an image graph.
Then, the accuracy of selecting image pairs is obtained by comparing the selected image pairs to the ground truth image graph.
In the off-line part, image representations of both BOW and VLAD are generated, and we further use BOW to construct an image graph, which is a structure containing relationships between the dataset images.
Then, an iterative re-ranking method is proposed to re-estimate the probabilities of relevance with the support of the image graph, and the final ranks of the images are obtained according to the values of probability values.
For a given image graph G=〈V,E,w〉, a path π a =〈t 1,t 2,…,t n =a〉 is a sequence of adjacent pixels with terminus at a pixel a.
You can check out my latest blog to understand how the Image Graph works to power advanced scenarios.
We call this approach GD model, which has two steps: Graph-step (Section 2.3 ): create an undirected graph G on the image (graph vertexes are image voxels) with edge weight calculated according to the geodesic metric function g, and then find the shortest path P with respect to a pair of 'defined' endnodes a and b of the skeleton curve.
Viable tumor burden was quantitated by in vivo imaging system (IVIS) of tumor bioluminescence and representative IVIS images, graphs of photon flux over time and at the end of the experiment, and bone metastasis histopathology are shown in Fig. 5a d.
Worse, the app will not let you insert images, graphs or photos, which will be a deal-killer for many business users.
