{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:WSCMCLI2WZNBVTTMIALYC5CJ62","short_pith_number":"pith:WSCMCLI2","canonical_record":{"source":{"id":"1602.01464","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-03T20:53:33Z","cross_cats_sorted":[],"title_canon_sha256":"3c3cc01ef279e41205d6f56979b4fb3bc645c9f49eb8aa30637ddad4226bd1f0","abstract_canon_sha256":"58af0f9d674de1fbcae241647ed5b16f22b9214c80db1cab22206a9a3fdb1461"},"schema_version":"1.0"},"canonical_sha256":"b484c12d1ab65a1ace6c4017817449f69f00480a314e7ef2a5095e5c78df3988","source":{"kind":"arxiv","id":"1602.01464","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.01464","created_at":"2026-05-18T01:21:18Z"},{"alias_kind":"arxiv_version","alias_value":"1602.01464v1","created_at":"2026-05-18T01:21:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.01464","created_at":"2026-05-18T01:21:18Z"},{"alias_kind":"pith_short_12","alias_value":"WSCMCLI2WZNB","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_16","alias_value":"WSCMCLI2WZNBVTTM","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_8","alias_value":"WSCMCLI2","created_at":"2026-05-18T12:30:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:WSCMCLI2WZNBVTTMIALYC5CJ62","target":"record","payload":{"canonical_record":{"source":{"id":"1602.01464","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-03T20:53:33Z","cross_cats_sorted":[],"title_canon_sha256":"3c3cc01ef279e41205d6f56979b4fb3bc645c9f49eb8aa30637ddad4226bd1f0","abstract_canon_sha256":"58af0f9d674de1fbcae241647ed5b16f22b9214c80db1cab22206a9a3fdb1461"},"schema_version":"1.0"},"canonical_sha256":"b484c12d1ab65a1ace6c4017817449f69f00480a314e7ef2a5095e5c78df3988","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:21:18.871217Z","signature_b64":"552F4p0gSOqRPbmQViISyrColvSVmFsPOiWfU2GaKugxHPMoRfXODQZj2ruvOabkpw7T7V9JYHpsCgDIyzCeCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b484c12d1ab65a1ace6c4017817449f69f00480a314e7ef2a5095e5c78df3988","last_reissued_at":"2026-05-18T01:21:18.870595Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:21:18.870595Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1602.01464","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":"2026-05-18T01:21:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W98oWWdahoTJ8+oDzYq/IAFJU3hZE33zCbWKP9hIW/4Zzvc7VDe8HdB03owk+XhrNm2qd77kfPERtw48hRQ7DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T15:55:59.201820Z"},"content_sha256":"cc04b05d7a971ab4ad1ed19bc4d1ada17652123b3de30f8a17b4e3f9d8955b5c","schema_version":"1.0","event_id":"sha256:cc04b05d7a971ab4ad1ed19bc4d1ada17652123b3de30f8a17b4e3f9d8955b5c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:WSCMCLI2WZNBVTTMIALYC5CJ62","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Latent-Class Hough Forests for 6 DoF Object Pose Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alykhan Tejani, Andreas Doumanoglou, Danhang Tang, Rigas Kouskouridas, Tae-Kyun Kim","submitted_at":"2016-02-03T20:53:33Z","abstract_excerpt":"In this paper we present Latent-Class Hough Forests, a method for object detection and 6 DoF pose estimation in heavily cluttered and occluded scenarios. We adapt a state of the art template matching feature into a scale-invariant patch descriptor and integrate it into a regression forest using a novel template-based split function. We train with positive samples only and we treat class distributions at the leaf nodes as latent variables. During testing we infer by iteratively updating these distributions, providing accurate estimation of background clutter and foreground occlusions and, thus,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.01464","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":"2026-05-18T01:21:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9zStEvVn9SjnIMFsnZ/SCHvEJtmByrUMttY0xWZ6SW6/To8ObGzGfvBrxppW4SsNalcJ3nL1XJtk+QWjzV4hCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T15:55:59.202152Z"},"content_sha256":"c3de2ecc695365ee05e18674fa5d01aca34d4e52c39aefd62282c91c5eb34c94","schema_version":"1.0","event_id":"sha256:c3de2ecc695365ee05e18674fa5d01aca34d4e52c39aefd62282c91c5eb34c94"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WSCMCLI2WZNBVTTMIALYC5CJ62/bundle.json","state_url":"https://pith.science/pith/WSCMCLI2WZNBVTTMIALYC5CJ62/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WSCMCLI2WZNBVTTMIALYC5CJ62/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":"2026-06-01T15:55:59Z","links":{"resolver":"https://pith.science/pith/WSCMCLI2WZNBVTTMIALYC5CJ62","bundle":"https://pith.science/pith/WSCMCLI2WZNBVTTMIALYC5CJ62/bundle.json","state":"https://pith.science/pith/WSCMCLI2WZNBVTTMIALYC5CJ62/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WSCMCLI2WZNBVTTMIALYC5CJ62/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:WSCMCLI2WZNBVTTMIALYC5CJ62","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":"58af0f9d674de1fbcae241647ed5b16f22b9214c80db1cab22206a9a3fdb1461","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-03T20:53:33Z","title_canon_sha256":"3c3cc01ef279e41205d6f56979b4fb3bc645c9f49eb8aa30637ddad4226bd1f0"},"schema_version":"1.0","source":{"id":"1602.01464","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.01464","created_at":"2026-05-18T01:21:18Z"},{"alias_kind":"arxiv_version","alias_value":"1602.01464v1","created_at":"2026-05-18T01:21:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.01464","created_at":"2026-05-18T01:21:18Z"},{"alias_kind":"pith_short_12","alias_value":"WSCMCLI2WZNB","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_16","alias_value":"WSCMCLI2WZNBVTTM","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_8","alias_value":"WSCMCLI2","created_at":"2026-05-18T12:30:51Z"}],"graph_snapshots":[{"event_id":"sha256:c3de2ecc695365ee05e18674fa5d01aca34d4e52c39aefd62282c91c5eb34c94","target":"graph","created_at":"2026-05-18T01:21:18Z","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 present Latent-Class Hough Forests, a method for object detection and 6 DoF pose estimation in heavily cluttered and occluded scenarios. We adapt a state of the art template matching feature into a scale-invariant patch descriptor and integrate it into a regression forest using a novel template-based split function. We train with positive samples only and we treat class distributions at the leaf nodes as latent variables. During testing we infer by iteratively updating these distributions, providing accurate estimation of background clutter and foreground occlusions and, thus,","authors_text":"Alykhan Tejani, Andreas Doumanoglou, Danhang Tang, Rigas Kouskouridas, Tae-Kyun Kim","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-03T20:53:33Z","title":"Latent-Class Hough Forests for 6 DoF Object Pose Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.01464","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:cc04b05d7a971ab4ad1ed19bc4d1ada17652123b3de30f8a17b4e3f9d8955b5c","target":"record","created_at":"2026-05-18T01:21:18Z","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":"58af0f9d674de1fbcae241647ed5b16f22b9214c80db1cab22206a9a3fdb1461","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-02-03T20:53:33Z","title_canon_sha256":"3c3cc01ef279e41205d6f56979b4fb3bc645c9f49eb8aa30637ddad4226bd1f0"},"schema_version":"1.0","source":{"id":"1602.01464","kind":"arxiv","version":1}},"canonical_sha256":"b484c12d1ab65a1ace6c4017817449f69f00480a314e7ef2a5095e5c78df3988","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b484c12d1ab65a1ace6c4017817449f69f00480a314e7ef2a5095e5c78df3988","first_computed_at":"2026-05-18T01:21:18.870595Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:21:18.870595Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"552F4p0gSOqRPbmQViISyrColvSVmFsPOiWfU2GaKugxHPMoRfXODQZj2ruvOabkpw7T7V9JYHpsCgDIyzCeCA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:21:18.871217Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.01464","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cc04b05d7a971ab4ad1ed19bc4d1ada17652123b3de30f8a17b4e3f9d8955b5c","sha256:c3de2ecc695365ee05e18674fa5d01aca34d4e52c39aefd62282c91c5eb34c94"],"state_sha256":"77194bf41565a76fb05cf51417ec15852d7c4367d068ce2ea71a270515445811"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rOtlArTKQB5Nq6+AQZLjAOMxJu0UDdXC2Xm27y5eaurmW/V+BZ2oBVwZQ3kz5Xr2wy3zF+omZncwo9G+xlQ2Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T15:55:59.203933Z","bundle_sha256":"4b3da5ae8bedd02cc92582dc2be8e405fc41926715a7eee4514c9cefd7b88640"}}