update README

README.md

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-lidar-labelling is a tool for automatic segmentation of raw lidar clouds based on image segmentation.
+lidar-labelling is a tool for automatic segmentation of dense lidar clouds based on image segmentation.
 
 Our labelling algorithm consists of two stages.
 
-The first stage is a preliminary segmentation - a naive transfer of segmentation from images (performed by the [SAM](https://github.com/facebookresearch/segment-anything) algorithm) to the cloud. Then multi-stage processing of the cloud is performed, which allows us to make the cloud more compact before the final labelling without losing points that are significant for labelling. The preprocessing stages include removing points whose corresponding pixels were not marked on a sequence of images, selection of points close to the sensors, removal of noise, cloud voxelization.
+The first stage is a initial segmentation - a naive transfer of segmentation from images (performed by the [SAM](https://github.com/facebookresearch/segment-anything) algorithm) to the cloud. Then multi-stage processing of the cloud is performed, which allows us to make the cloud more compact before the final labelling without losing points that are significant for labelling. The preprocessing stages include removing points whose corresponding pixels were not marked on a sequence of images, selection of points close to the sensors, removal of noise, cloud voxelization.
 
 The next stage is segmentation itself. The segmentation criterion in this work is the distance between points, which is calculated through the physical distance and the degree of similarity of the labelling of points on several images. Based on the distance matrix, the prepared cloud is segmented using the [GraphCut](https://ieeexplore.ieee.org/abstract/document/937505) algorithm.