PatchMatch-Based Automatic Lattice Detection for Near-Regular Textures
In this work, we investigate the problem of automatically inferring the lattice structure of near-regular textures (NRT) in real-world images. Our technique leverages the PatchMatch algorithm for finding k-nearest-neighbor (kNN) correspondences in an image. We use these kNNs to recover an initial estimate of the 2D wallpaper basis vectors, and seed vertices of the texture lattice. We iteratively expand this lattice by solving an MRF optimization problem. We show that we can discretize the space of good solutions for the MRF using the kNNs, allowing us to efficiently and accurately optimize the MRF energy function using the Particle Belief Propagation algorithm. We demonstrate our technique on a benchmark NRT dataset containing a wide range of images with geometric and photometric variations, and show that our method clearly outperforms the state of the art in terms of both texel detection rate and texel localization score.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
PatchmatchNet: Learned Multi-View Patchmatch Stereo
We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo. With high computation speed and low memory requirement, PatchmatchNet can process higher resolution…
3D ReconstructionPoint CloudsPatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility
Recent learning-based multi-view stereo (MVS) methods show excellent performance with dense cameras and small depth ranges. However, non-learning based approaches still outperform for scenes with large depth ranges and s…
On the Convergence of PatchMatch and Its Variants
Many problems in image/video processing and computer vision require the computation of a dense k-nearest neighbor field (k-NNF) between two images. For each patch in a query image, the k-NNF determines the positions of t…
Closed-set lattice of regular sets based on a serial and transitive relation through matroids
Rough sets are efficient for data pre-processing in data mining. Matroids are based on linear algebra and graph theory, and have a variety of applications in many fields. Both rough sets and matroids are closely related …
AllRelationSuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches
Superpixels have become very popular in many computer vision applications. Nevertheless, they remain underexploited since the superpixel decomposition may produce irregular and non stable segmentation results due to the …
Image SegmentationMedical Image SegmentationSegmentationSemantic Segmentation+1