{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:3336IL6IUZ3YDYCYH66OCEALRH","short_pith_number":"pith:3336IL6I","canonical_record":{"source":{"id":"1709.09550","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-26T15:15:52Z","cross_cats_sorted":[],"title_canon_sha256":"47fa24da77388abc352b80464f015b627aab883b37b6213e8eadaae4a663a8d2","abstract_canon_sha256":"8cbe2cf1070227ae7ac95016d850c01f730e24384ac649bdd5035b0f26b66059"},"schema_version":"1.0"},"canonical_sha256":"def7e42fc8a67781e0583fbce1100b89cc8a1da4e50604abd89a978f282cb277","source":{"kind":"arxiv","id":"1709.09550","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.09550","created_at":"2026-05-18T00:34:11Z"},{"alias_kind":"arxiv_version","alias_value":"1709.09550v1","created_at":"2026-05-18T00:34:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.09550","created_at":"2026-05-18T00:34:11Z"},{"alias_kind":"pith_short_12","alias_value":"3336IL6IUZ3Y","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"3336IL6IUZ3YDYCY","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"3336IL6I","created_at":"2026-05-18T12:30:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:3336IL6IUZ3YDYCYH66OCEALRH","target":"record","payload":{"canonical_record":{"source":{"id":"1709.09550","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-26T15:15:52Z","cross_cats_sorted":[],"title_canon_sha256":"47fa24da77388abc352b80464f015b627aab883b37b6213e8eadaae4a663a8d2","abstract_canon_sha256":"8cbe2cf1070227ae7ac95016d850c01f730e24384ac649bdd5035b0f26b66059"},"schema_version":"1.0"},"canonical_sha256":"def7e42fc8a67781e0583fbce1100b89cc8a1da4e50604abd89a978f282cb277","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:11.336905Z","signature_b64":"MGjI8KSnIZ5cMOoidvOsZqLnNpyVcBza44HPpuyuSNIJMV1kqYL0ikA/RXua1HHRtvTmh8EBwfYSD5eli+gLDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"def7e42fc8a67781e0583fbce1100b89cc8a1da4e50604abd89a978f282cb277","last_reissued_at":"2026-05-18T00:34:11.336416Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:11.336416Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.09550","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":"2026-05-18T00:34:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F8MmeqyWfnda1bxIQE93iOyHKk0FEWSI89HTt+fbuBRK7lTYcJvMz9dmOCMzP9fKTN3jsI04Z36PK+DfnWAXCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T08:11:40.270437Z"},"content_sha256":"6003964a180f70d94f7acabcaaafa294584475e724a2a2e2b7b437b5c82de06f","schema_version":"1.0","event_id":"sha256:6003964a180f70d94f7acabcaaafa294584475e724a2a2e2b7b437b5c82de06f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:3336IL6IUZ3YDYCYH66OCEALRH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scale Adaptive Clustering of Multiple Structures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Peter Meer, Xiang Yang","submitted_at":"2017-09-26T15:15:52Z","abstract_excerpt":"We propose the segmentation of noisy datasets into Multiple Inlier Structures with a new Robust Estimator (MISRE). The scale of each individual structure is estimated adaptively from the input data and refined by mean shift, without tuning any parameter in the process, or manually specifying thresholds for different estimation problems. Once all the data points were classified into separate structures, these structures are sorted by their densities with the strongest inlier structures coming out first. Several 2D and 3D synthetic and real examples are presented to illustrate the efficiency, ro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.09550","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":"2026-05-18T00:34:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j79yr+MDW3Y9PHFu9AVtKdUCIv1oo8DhsO7MrLW4QXIj0fDQMimVTyZaovKFvR4kEVYdRr92b0GwKmxpa3jZAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T08:11:40.271067Z"},"content_sha256":"12aef0345d09a54fa51effa31244d10e176e02b050b0a2efd4cad0793bdaa6ba","schema_version":"1.0","event_id":"sha256:12aef0345d09a54fa51effa31244d10e176e02b050b0a2efd4cad0793bdaa6ba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3336IL6IUZ3YDYCYH66OCEALRH/bundle.json","state_url":"https://pith.science/pith/3336IL6IUZ3YDYCYH66OCEALRH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3336IL6IUZ3YDYCYH66OCEALRH/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":"2026-05-27T08:11:40Z","links":{"resolver":"https://pith.science/pith/3336IL6IUZ3YDYCYH66OCEALRH","bundle":"https://pith.science/pith/3336IL6IUZ3YDYCYH66OCEALRH/bundle.json","state":"https://pith.science/pith/3336IL6IUZ3YDYCYH66OCEALRH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3336IL6IUZ3YDYCYH66OCEALRH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:3336IL6IUZ3YDYCYH66OCEALRH","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":"8cbe2cf1070227ae7ac95016d850c01f730e24384ac649bdd5035b0f26b66059","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-26T15:15:52Z","title_canon_sha256":"47fa24da77388abc352b80464f015b627aab883b37b6213e8eadaae4a663a8d2"},"schema_version":"1.0","source":{"id":"1709.09550","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.09550","created_at":"2026-05-18T00:34:11Z"},{"alias_kind":"arxiv_version","alias_value":"1709.09550v1","created_at":"2026-05-18T00:34:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.09550","created_at":"2026-05-18T00:34:11Z"},{"alias_kind":"pith_short_12","alias_value":"3336IL6IUZ3Y","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"3336IL6IUZ3YDYCY","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"3336IL6I","created_at":"2026-05-18T12:30:55Z"}],"graph_snapshots":[{"event_id":"sha256:12aef0345d09a54fa51effa31244d10e176e02b050b0a2efd4cad0793bdaa6ba","target":"graph","created_at":"2026-05-18T00:34:11Z","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":"We propose the segmentation of noisy datasets into Multiple Inlier Structures with a new Robust Estimator (MISRE). The scale of each individual structure is estimated adaptively from the input data and refined by mean shift, without tuning any parameter in the process, or manually specifying thresholds for different estimation problems. Once all the data points were classified into separate structures, these structures are sorted by their densities with the strongest inlier structures coming out first. Several 2D and 3D synthetic and real examples are presented to illustrate the efficiency, ro","authors_text":"Peter Meer, Xiang Yang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-26T15:15:52Z","title":"Scale Adaptive Clustering of Multiple Structures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.09550","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":"sha256:6003964a180f70d94f7acabcaaafa294584475e724a2a2e2b7b437b5c82de06f","target":"record","created_at":"2026-05-18T00:34:11Z","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":"8cbe2cf1070227ae7ac95016d850c01f730e24384ac649bdd5035b0f26b66059","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-26T15:15:52Z","title_canon_sha256":"47fa24da77388abc352b80464f015b627aab883b37b6213e8eadaae4a663a8d2"},"schema_version":"1.0","source":{"id":"1709.09550","kind":"arxiv","version":1}},"canonical_sha256":"def7e42fc8a67781e0583fbce1100b89cc8a1da4e50604abd89a978f282cb277","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"def7e42fc8a67781e0583fbce1100b89cc8a1da4e50604abd89a978f282cb277","first_computed_at":"2026-05-18T00:34:11.336416Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:34:11.336416Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MGjI8KSnIZ5cMOoidvOsZqLnNpyVcBza44HPpuyuSNIJMV1kqYL0ikA/RXua1HHRtvTmh8EBwfYSD5eli+gLDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:34:11.336905Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.09550","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6003964a180f70d94f7acabcaaafa294584475e724a2a2e2b7b437b5c82de06f","sha256:12aef0345d09a54fa51effa31244d10e176e02b050b0a2efd4cad0793bdaa6ba"],"state_sha256":"98441d9932f9f7ad5297808f05beb84a7ab0e6ff6fefc01f26c8b5758cbad859"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eQ9Yebz+sX3Q2gXdXbrWpFs1WmWiXeQojte2bPLJhSH9aJEfQpEOBcGLeXfiROvtlX7aRS8P5Ag2nqngzSWzBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T08:11:40.274600Z","bundle_sha256":"ee1170f5dc6c0b9ea757b6b7926466271642dc8d2ee442caf87461b1ef76785a"}}