{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:ETP6FNTXCURON7TYVOBDAR6T5A","short_pith_number":"pith:ETP6FNTX","canonical_record":{"source":{"id":"1404.5765","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-23T09:48:30Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"461a93cc10e3998b286a185094637d479f178155a1ef70d447b220077f543beb","abstract_canon_sha256":"9f39b0cfbc150b71d815281200d84ce2355364f7994173fe022b8766b4927b11"},"schema_version":"1.0"},"canonical_sha256":"24dfe2b6771522e6fe78ab823047d3e828766f4eee8bdab2123a4fd8b0d99fda","source":{"kind":"arxiv","id":"1404.5765","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1404.5765","created_at":"2026-05-18T02:53:27Z"},{"alias_kind":"arxiv_version","alias_value":"1404.5765v1","created_at":"2026-05-18T02:53:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.5765","created_at":"2026-05-18T02:53:27Z"},{"alias_kind":"pith_short_12","alias_value":"ETP6FNTXCURO","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_16","alias_value":"ETP6FNTXCURON7TY","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_8","alias_value":"ETP6FNTX","created_at":"2026-05-18T12:28:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:ETP6FNTXCURON7TYVOBDAR6T5A","target":"record","payload":{"canonical_record":{"source":{"id":"1404.5765","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-23T09:48:30Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"461a93cc10e3998b286a185094637d479f178155a1ef70d447b220077f543beb","abstract_canon_sha256":"9f39b0cfbc150b71d815281200d84ce2355364f7994173fe022b8766b4927b11"},"schema_version":"1.0"},"canonical_sha256":"24dfe2b6771522e6fe78ab823047d3e828766f4eee8bdab2123a4fd8b0d99fda","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:53:27.980935Z","signature_b64":"GYL8Qq4Qomp+9RXuF6HxSaUo7wucjlx+ETeAcsIGbEotsPP+J8c2LVcvW4LHvnuun1sADYaCMp0SiYqjZ0mVDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"24dfe2b6771522e6fe78ab823047d3e828766f4eee8bdab2123a4fd8b0d99fda","last_reissued_at":"2026-05-18T02:53:27.980158Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:53:27.980158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1404.5765","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":"2026-05-18T02:53:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uo1XwldJ+LmkbgREbZaEfP4xDO3kkRDf4nI5RrU9Ca2XrkS66CkwZA0PNc8/AYBGneRN6dTA/z7A9GbgSQxcBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T08:12:13.504891Z"},"content_sha256":"d38700f319afbd200961e76ee9af38a7d6c41bf58511bc5f204a3af1f8add921","schema_version":"1.0","event_id":"sha256:d38700f319afbd200961e76ee9af38a7d6c41bf58511bc5f204a3af1f8add921"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:ETP6FNTXCURON7TYVOBDAR6T5A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Find my mug: Efficient object search with a mobile robot using semantic segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Daniel Wolf, Johann Prankl, Markus Bajones, Markus Vincze","submitted_at":"2014-04-23T09:48:30Z","abstract_excerpt":"In this paper, we propose an efficient semantic segmentation framework for indoor scenes, tailored to the application on a mobile robot. Semantic segmentation can help robots to gain a reasonable understanding of their environment, but to reach this goal, the algorithms not only need to be accurate, but also fast and robust. Therefore, we developed an optimized 3D point cloud processing framework based on a Randomized Decision Forest, achieving competitive results at sufficiently high frame rates. We evaluate the capabilities of our method on the popular NYU depth dataset and our own data and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.5765","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":"2026-05-18T02:53:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IuikwPRfI0S94pv+t6t3xEoFGAZOMjDJq+ARNpDrXmS9Dzg/LoRm91lR50AY901K/WarDLhj6/iYHo+lAnPEAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T08:12:13.505238Z"},"content_sha256":"5acf9aa8aeaa84e1f95fc8f2e82ad20bf4362527bedc6fca90fa0a8e7d431d94","schema_version":"1.0","event_id":"sha256:5acf9aa8aeaa84e1f95fc8f2e82ad20bf4362527bedc6fca90fa0a8e7d431d94"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ETP6FNTXCURON7TYVOBDAR6T5A/bundle.json","state_url":"https://pith.science/pith/ETP6FNTXCURON7TYVOBDAR6T5A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ETP6FNTXCURON7TYVOBDAR6T5A/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":"2026-06-21T08:12:13Z","links":{"resolver":"https://pith.science/pith/ETP6FNTXCURON7TYVOBDAR6T5A","bundle":"https://pith.science/pith/ETP6FNTXCURON7TYVOBDAR6T5A/bundle.json","state":"https://pith.science/pith/ETP6FNTXCURON7TYVOBDAR6T5A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ETP6FNTXCURON7TYVOBDAR6T5A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:ETP6FNTXCURON7TYVOBDAR6T5A","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":"9f39b0cfbc150b71d815281200d84ce2355364f7994173fe022b8766b4927b11","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-23T09:48:30Z","title_canon_sha256":"461a93cc10e3998b286a185094637d479f178155a1ef70d447b220077f543beb"},"schema_version":"1.0","source":{"id":"1404.5765","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1404.5765","created_at":"2026-05-18T02:53:27Z"},{"alias_kind":"arxiv_version","alias_value":"1404.5765v1","created_at":"2026-05-18T02:53:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.5765","created_at":"2026-05-18T02:53:27Z"},{"alias_kind":"pith_short_12","alias_value":"ETP6FNTXCURO","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_16","alias_value":"ETP6FNTXCURON7TY","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_8","alias_value":"ETP6FNTX","created_at":"2026-05-18T12:28:28Z"}],"graph_snapshots":[{"event_id":"sha256:5acf9aa8aeaa84e1f95fc8f2e82ad20bf4362527bedc6fca90fa0a8e7d431d94","target":"graph","created_at":"2026-05-18T02:53:27Z","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":"In this paper, we propose an efficient semantic segmentation framework for indoor scenes, tailored to the application on a mobile robot. Semantic segmentation can help robots to gain a reasonable understanding of their environment, but to reach this goal, the algorithms not only need to be accurate, but also fast and robust. Therefore, we developed an optimized 3D point cloud processing framework based on a Randomized Decision Forest, achieving competitive results at sufficiently high frame rates. We evaluate the capabilities of our method on the popular NYU depth dataset and our own data and ","authors_text":"Daniel Wolf, Johann Prankl, Markus Bajones, Markus Vincze","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-23T09:48:30Z","title":"Find my mug: Efficient object search with a mobile robot using semantic segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.5765","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:d38700f319afbd200961e76ee9af38a7d6c41bf58511bc5f204a3af1f8add921","target":"record","created_at":"2026-05-18T02:53:27Z","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":"9f39b0cfbc150b71d815281200d84ce2355364f7994173fe022b8766b4927b11","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-23T09:48:30Z","title_canon_sha256":"461a93cc10e3998b286a185094637d479f178155a1ef70d447b220077f543beb"},"schema_version":"1.0","source":{"id":"1404.5765","kind":"arxiv","version":1}},"canonical_sha256":"24dfe2b6771522e6fe78ab823047d3e828766f4eee8bdab2123a4fd8b0d99fda","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"24dfe2b6771522e6fe78ab823047d3e828766f4eee8bdab2123a4fd8b0d99fda","first_computed_at":"2026-05-18T02:53:27.980158Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:53:27.980158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GYL8Qq4Qomp+9RXuF6HxSaUo7wucjlx+ETeAcsIGbEotsPP+J8c2LVcvW4LHvnuun1sADYaCMp0SiYqjZ0mVDw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:53:27.980935Z","signed_message":"canonical_sha256_bytes"},"source_id":"1404.5765","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d38700f319afbd200961e76ee9af38a7d6c41bf58511bc5f204a3af1f8add921","sha256:5acf9aa8aeaa84e1f95fc8f2e82ad20bf4362527bedc6fca90fa0a8e7d431d94"],"state_sha256":"0da9f2d6117b98d1cd356e2a16aa9770656b1026529e2502c15e458b589e520b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q8PMVJZgDIH2EzCutxSHwNm7cuuTVQ40wbcyGA7LcpU8nZKVAK0XV/s+31bmM0L4fDXMcShUEfIsR2Eq0x4ODQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T08:12:13.507212Z","bundle_sha256":"a3279597946ea9fe32105973ed32399633ab2ca70a8965c2303f57f18839769b"}}