Latent Semantic Consensus For Deterministic Geometric Model Fitting

arXiv:2403.06444v1 Announce Type: new
Abstract: Estimating reliable geometric model parameters from the data with severe outliers is a fundamental and important task in computer vision. This paper attempts to sample high-quality subsets and select model instances to estimate parameters in the multi-structural data. To address this, we propose an effective method called Latent Semantic Consensus (LSC). The principle of LSC is to preserve the latent semantic consensus in both data points and model hypotheses. Specifically, LSC formulates the model fitting …

arxiv consensus cs.cv semantic type