{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:LKZHAWOBFATBPBBT4XDFGDCY3O","short_pith_number":"pith:LKZHAWOB","schema_version":"1.0","canonical_sha256":"5ab27059c12826178433e5c6530c58dba17f0d31106a76b49142fe591ae82f2a","source":{"kind":"arxiv","id":"1805.11219","version":2},"attestation_state":"computed","paper":{"title":"Non-rigid Reconstruction with a Single Moving RGB-D Camera","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Clinton Fookes, Mark Cox, Peyman Moghadam, Shafeeq Elanattil, Sridha Sridharan","submitted_at":"2018-05-29T02:23:30Z","abstract_excerpt":"We present a novel non-rigid reconstruction method using a moving RGB-D camera. Current approaches use only non-rigid part of the scene and completely ignore the rigid background. Non-rigid parts often lack sufficient geometric and photometric information for tracking large frame-to-frame motion. Our approach uses camera pose estimated from the rigid background for foreground tracking. This enables robust foreground tracking in situations where large frame-to-frame motion occurs. Moreover, we are proposing a multi-scale deformation graph which improves non-rigid tracking without compromising t"},"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":"1805.11219","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-29T02:23:30Z","cross_cats_sorted":[],"title_canon_sha256":"c9c8f04cc1fc46020acecb1033bcb0075c6d7bf1ab80c1c2db08246165fe39fd","abstract_canon_sha256":"e3908ed5b2e3423ddab7f18fdd9c09f3dfaedaa152920d519ccdd06710768229"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:37.348133Z","signature_b64":"Fm6l4wKJ2w+Aq3JvE2ihWFDMpTFZowddaAtNDWdXQyIxUGne/FItCqYYrz9rPVTp36qK2KMzb09l/1kbmx3SCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5ab27059c12826178433e5c6530c58dba17f0d31106a76b49142fe591ae82f2a","last_reissued_at":"2026-05-18T00:14:37.347308Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:37.347308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Non-rigid Reconstruction with a Single Moving RGB-D Camera","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Clinton Fookes, Mark Cox, Peyman Moghadam, Shafeeq Elanattil, Sridha Sridharan","submitted_at":"2018-05-29T02:23:30Z","abstract_excerpt":"We present a novel non-rigid reconstruction method using a moving RGB-D camera. Current approaches use only non-rigid part of the scene and completely ignore the rigid background. Non-rigid parts often lack sufficient geometric and photometric information for tracking large frame-to-frame motion. Our approach uses camera pose estimated from the rigid background for foreground tracking. This enables robust foreground tracking in situations where large frame-to-frame motion occurs. Moreover, we are proposing a multi-scale deformation graph which improves non-rigid tracking without compromising t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.11219","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1805.11219","created_at":"2026-05-18T00:14:37.347465+00:00"},{"alias_kind":"arxiv_version","alias_value":"1805.11219v2","created_at":"2026-05-18T00:14:37.347465+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.11219","created_at":"2026-05-18T00:14:37.347465+00:00"},{"alias_kind":"pith_short_12","alias_value":"LKZHAWOBFATB","created_at":"2026-05-18T12:32:37.024351+00:00"},{"alias_kind":"pith_short_16","alias_value":"LKZHAWOBFATBPBBT","created_at":"2026-05-18T12:32:37.024351+00:00"},{"alias_kind":"pith_short_8","alias_value":"LKZHAWOB","created_at":"2026-05-18T12:32:37.024351+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/LKZHAWOBFATBPBBT4XDFGDCY3O","json":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O.json","graph_json":"https://pith.science/api/pith-number/LKZHAWOBFATBPBBT4XDFGDCY3O/graph.json","events_json":"https://pith.science/api/pith-number/LKZHAWOBFATBPBBT4XDFGDCY3O/events.json","paper":"https://pith.science/paper/LKZHAWOB"},"agent_actions":{"view_html":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O","download_json":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O.json","view_paper":"https://pith.science/paper/LKZHAWOB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1805.11219&json=true","fetch_graph":"https://pith.science/api/pith-number/LKZHAWOBFATBPBBT4XDFGDCY3O/graph.json","fetch_events":"https://pith.science/api/pith-number/LKZHAWOBFATBPBBT4XDFGDCY3O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O/action/storage_attestation","attest_author":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O/action/author_attestation","sign_citation":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O/action/citation_signature","submit_replication":"https://pith.science/pith/LKZHAWOBFATBPBBT4XDFGDCY3O/action/replication_record"}},"created_at":"2026-05-18T00:14:37.347465+00:00","updated_at":"2026-05-18T00:14:37.347465+00:00"}