{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:XR2KHNYFIMUVO4Z2VRDRMNZ6W4","short_pith_number":"pith:XR2KHNYF","canonical_record":{"source":{"id":"1708.00514","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T21:07:14Z","cross_cats_sorted":[],"title_canon_sha256":"7f74c8473fccfba5cd9b090cf5250445fc684b0ed56b699753095f1f7c898c5b","abstract_canon_sha256":"39eddea74329a4a2011c0b09364c65ea4aa83422d2211e2fb91c0def514ea56b"},"schema_version":"1.0"},"canonical_sha256":"bc74a3b705432957733aac4716373eb7133cf4485b00668bf18fac05e151e2fd","source":{"kind":"arxiv","id":"1708.00514","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.00514","created_at":"2026-05-18T00:38:45Z"},{"alias_kind":"arxiv_version","alias_value":"1708.00514v1","created_at":"2026-05-18T00:38:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.00514","created_at":"2026-05-18T00:38:45Z"},{"alias_kind":"pith_short_12","alias_value":"XR2KHNYFIMUV","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XR2KHNYFIMUVO4Z2","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XR2KHNYF","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:XR2KHNYFIMUVO4Z2VRDRMNZ6W4","target":"record","payload":{"canonical_record":{"source":{"id":"1708.00514","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T21:07:14Z","cross_cats_sorted":[],"title_canon_sha256":"7f74c8473fccfba5cd9b090cf5250445fc684b0ed56b699753095f1f7c898c5b","abstract_canon_sha256":"39eddea74329a4a2011c0b09364c65ea4aa83422d2211e2fb91c0def514ea56b"},"schema_version":"1.0"},"canonical_sha256":"bc74a3b705432957733aac4716373eb7133cf4485b00668bf18fac05e151e2fd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:45.550560Z","signature_b64":"spiz6wrRUoGmGALWPYCE07C5Q/eBQdFUG1WuseOgS8M35jGs9sdULS4Nelack6S/T02mFOBuWv74D0A0QKyqCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc74a3b705432957733aac4716373eb7133cf4485b00668bf18fac05e151e2fd","last_reissued_at":"2026-05-18T00:38:45.550016Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:45.550016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.00514","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:38:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YyDor9IxYlPaeay5ppHRctfDR001CKdIFlJQIx7RabDVpeMkQVIh1ukO3I6FyAb53ugZtjfkv98+HKR2A3kyBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T04:14:23.159517Z"},"content_sha256":"0034180f49cf818fac16311515ea38adbef75887d4335b6a9aadcc9df844f32b","schema_version":"1.0","event_id":"sha256:0034180f49cf818fac16311515ea38adbef75887d4335b6a9aadcc9df844f32b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:XR2KHNYFIMUVO4Z2VRDRMNZ6W4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dense Piecewise Planar RGB-D SLAM for Indoor Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jana Kosecka, Phi-Hung Le","submitted_at":"2017-08-01T21:07:14Z","abstract_excerpt":"The paper exploits weak Manhattan constraints to parse the structure of indoor environments from RGB-D video sequences in an online setting. We extend the previous approach for single view parsing of indoor scenes to video sequences and formulate the problem of recovering the floor plan of the environment as an optimal labeling problem solved using dynamic programming. The temporal continuity is enforced in a recursive setting, where labeling from previous frames is used as a prior term in the objective function. In addition to recovery of piecewise planar weak Manhattan structure of the exten"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.00514","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:38:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j/A3w4dbc2a+qoeoycG2pXroZHzBt8L36Y0O4q7sYQJB2IAwzYjblt6+DpIs+B4CX/H6ZWXRtqnx+dbC1FcSBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T04:14:23.160144Z"},"content_sha256":"4474028e956fc1c8b98d83d42e5c620958f56e889e49cbe4c7edb4a60f91ccbd","schema_version":"1.0","event_id":"sha256:4474028e956fc1c8b98d83d42e5c620958f56e889e49cbe4c7edb4a60f91ccbd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XR2KHNYFIMUVO4Z2VRDRMNZ6W4/bundle.json","state_url":"https://pith.science/pith/XR2KHNYFIMUVO4Z2VRDRMNZ6W4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XR2KHNYFIMUVO4Z2VRDRMNZ6W4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-08T04:14:23Z","links":{"resolver":"https://pith.science/pith/XR2KHNYFIMUVO4Z2VRDRMNZ6W4","bundle":"https://pith.science/pith/XR2KHNYFIMUVO4Z2VRDRMNZ6W4/bundle.json","state":"https://pith.science/pith/XR2KHNYFIMUVO4Z2VRDRMNZ6W4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XR2KHNYFIMUVO4Z2VRDRMNZ6W4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:XR2KHNYFIMUVO4Z2VRDRMNZ6W4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"39eddea74329a4a2011c0b09364c65ea4aa83422d2211e2fb91c0def514ea56b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T21:07:14Z","title_canon_sha256":"7f74c8473fccfba5cd9b090cf5250445fc684b0ed56b699753095f1f7c898c5b"},"schema_version":"1.0","source":{"id":"1708.00514","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.00514","created_at":"2026-05-18T00:38:45Z"},{"alias_kind":"arxiv_version","alias_value":"1708.00514v1","created_at":"2026-05-18T00:38:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.00514","created_at":"2026-05-18T00:38:45Z"},{"alias_kind":"pith_short_12","alias_value":"XR2KHNYFIMUV","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"XR2KHNYFIMUVO4Z2","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"XR2KHNYF","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:4474028e956fc1c8b98d83d42e5c620958f56e889e49cbe4c7edb4a60f91ccbd","target":"graph","created_at":"2026-05-18T00:38:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"The paper exploits weak Manhattan constraints to parse the structure of indoor environments from RGB-D video sequences in an online setting. We extend the previous approach for single view parsing of indoor scenes to video sequences and formulate the problem of recovering the floor plan of the environment as an optimal labeling problem solved using dynamic programming. The temporal continuity is enforced in a recursive setting, where labeling from previous frames is used as a prior term in the objective function. In addition to recovery of piecewise planar weak Manhattan structure of the exten","authors_text":"Jana Kosecka, Phi-Hung Le","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T21:07:14Z","title":"Dense Piecewise Planar RGB-D SLAM for Indoor Environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.00514","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0034180f49cf818fac16311515ea38adbef75887d4335b6a9aadcc9df844f32b","target":"record","created_at":"2026-05-18T00:38:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"39eddea74329a4a2011c0b09364c65ea4aa83422d2211e2fb91c0def514ea56b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T21:07:14Z","title_canon_sha256":"7f74c8473fccfba5cd9b090cf5250445fc684b0ed56b699753095f1f7c898c5b"},"schema_version":"1.0","source":{"id":"1708.00514","kind":"arxiv","version":1}},"canonical_sha256":"bc74a3b705432957733aac4716373eb7133cf4485b00668bf18fac05e151e2fd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc74a3b705432957733aac4716373eb7133cf4485b00668bf18fac05e151e2fd","first_computed_at":"2026-05-18T00:38:45.550016Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:45.550016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"spiz6wrRUoGmGALWPYCE07C5Q/eBQdFUG1WuseOgS8M35jGs9sdULS4Nelack6S/T02mFOBuWv74D0A0QKyqCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:45.550560Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.00514","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0034180f49cf818fac16311515ea38adbef75887d4335b6a9aadcc9df844f32b","sha256:4474028e956fc1c8b98d83d42e5c620958f56e889e49cbe4c7edb4a60f91ccbd"],"state_sha256":"115fb91218ee99637f5a85e70d98ab99ee6e028281491f5a1e5c02a2d268950a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/nFuq8RdEfzspvgcDzoD//uHg1TR2TPGqt3Tt85p6Ybz3T/Z0ySwleV/eUxkwWALEUK2qng/iHmgdAiVJfA5CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T04:14:23.163702Z","bundle_sha256":"f0a87a71894836abcf328245322f042c9167a7265979d98760d2e71c838064cc"}}