Fast and effective variant calling algorithms have been crucial to the successful application of DNA sequencing in human genetics. In particular, joint calling – in which reads from multiple individuals are pooled to increase power for shared variants – is an important tool for population surveys of variation. Joint calling was applied by the 1000 Genomes Project to identify variants across many individuals each sequenced to low coverage (about 5-fold). This approach successfully found common small variants, but broadly missed structural variants and large indels for which short-read sequencing has limited sensitivity. To support use of large variants in rare disease and common trait association studies, it is necessary to perform population-scale surveys with a technology effective at detecting indels and structural variants, such as PacBio SMRT Sequencing. For these studies, it is important to have a joint calling workflow that works with PacBio reads. We have developed pbsv, an indel and structural variant caller for PacBio reads, that provides a two-step joint calling workflow similar to that used to build the ExAC database. The first stage, discovery, is performed separately for each sample and consolidates whole genome alignments into a sparse representation of potentially variant loci. The second stage, calling, is performed on all samples together and considers only the signatures identified in the discovery stage. We applied the pbsv joint calling workflow to PacBio reads from twenty human genomes, with coverage ranging from 5-fold to 80-fold per sample for a total of 460-fold. The analysis required only 102 CPU hours, and identified over 800,000 indels and structural variants, including hundreds of inversions and translocations, many times more than discovered with short-read sequencing. The workflow is scalable to thousands of samples. The ongoing application of this workflow to thousands of samples will provide insight into the evolution and functional importance of large variants in human evolution and disease.