{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:SQ7MBWPYSXU5REW6JGLMMPVZPO","short_pith_number":"pith:SQ7MBWPY","schema_version":"1.0","canonical_sha256":"943ec0d9f895e9d892de4996c63eb97bb797f1c811bec1f7a6cf6b6444af7f46","source":{"kind":"arxiv","id":"2109.08224","version":1},"attestation_state":"computed","paper":{"title":"A Divide-and-Merge Point Cloud Clustering Algorithm for LiDAR Panoptic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Xiao Zhang, Xinming Huang, Yiming Zhao","submitted_at":"2021-09-16T21:15:25Z","abstract_excerpt":"Clustering objects from the LiDAR point cloud is an important research problem with many applications such as autonomous driving. To meet the real-time requirement, existing research proposed to apply the connected-component-labeling (CCL) technique on LiDAR spherical range image with a heuristic condition to check if two neighbor points are connected. However, LiDAR range image is different from a binary image which has a deterministic condition to tell if two pixels belong to the same component. The heuristic condition used on the LiDAR range image only works empirically, which suggests the "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2109.08224","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-09-16T21:15:25Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"68653e1540899a1eb56210aa4de20dbd5e4d6339e40d890a1e006b2ea2bc17d3","abstract_canon_sha256":"067394bef9235dcc037966a58949da8e670f0e5e9baf3ce52ae2b1c1632fe008"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:15:13.286818Z","signature_b64":"hsuaj2SY/Z1ElW+j+6l/6O4IJ94Hs201jYlZPMeLmUw1bDeyCKZlcaRmPYjbqTKZH8KUphPOiVLy2zaWa2reDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"943ec0d9f895e9d892de4996c63eb97bb797f1c811bec1f7a6cf6b6444af7f46","last_reissued_at":"2026-07-05T03:15:13.286474Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:15:13.286474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Divide-and-Merge Point Cloud Clustering Algorithm for LiDAR Panoptic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Xiao Zhang, Xinming Huang, Yiming Zhao","submitted_at":"2021-09-16T21:15:25Z","abstract_excerpt":"Clustering objects from the LiDAR point cloud is an important research problem with many applications such as autonomous driving. To meet the real-time requirement, existing research proposed to apply the connected-component-labeling (CCL) technique on LiDAR spherical range image with a heuristic condition to check if two neighbor points are connected. However, LiDAR range image is different from a binary image which has a deterministic condition to tell if two pixels belong to the same component. The heuristic condition used on the LiDAR range image only works empirically, which suggests the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.08224","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2109.08224/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2109.08224","created_at":"2026-07-05T03:15:13.286536+00:00"},{"alias_kind":"arxiv_version","alias_value":"2109.08224v1","created_at":"2026-07-05T03:15:13.286536+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.08224","created_at":"2026-07-05T03:15:13.286536+00:00"},{"alias_kind":"pith_short_12","alias_value":"SQ7MBWPYSXU5","created_at":"2026-07-05T03:15:13.286536+00:00"},{"alias_kind":"pith_short_16","alias_value":"SQ7MBWPYSXU5REW6","created_at":"2026-07-05T03:15:13.286536+00:00"},{"alias_kind":"pith_short_8","alias_value":"SQ7MBWPY","created_at":"2026-07-05T03:15:13.286536+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO","json":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO.json","graph_json":"https://pith.science/api/pith-number/SQ7MBWPYSXU5REW6JGLMMPVZPO/graph.json","events_json":"https://pith.science/api/pith-number/SQ7MBWPYSXU5REW6JGLMMPVZPO/events.json","paper":"https://pith.science/paper/SQ7MBWPY"},"agent_actions":{"view_html":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO","download_json":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO.json","view_paper":"https://pith.science/paper/SQ7MBWPY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2109.08224&json=true","fetch_graph":"https://pith.science/api/pith-number/SQ7MBWPYSXU5REW6JGLMMPVZPO/graph.json","fetch_events":"https://pith.science/api/pith-number/SQ7MBWPYSXU5REW6JGLMMPVZPO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO/action/storage_attestation","attest_author":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO/action/author_attestation","sign_citation":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO/action/citation_signature","submit_replication":"https://pith.science/pith/SQ7MBWPYSXU5REW6JGLMMPVZPO/action/replication_record"}},"created_at":"2026-07-05T03:15:13.286536+00:00","updated_at":"2026-07-05T03:15:13.286536+00:00"}