{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:IWFYYI3WPX4AZNRNVFS6XLEW27","short_pith_number":"pith:IWFYYI3W","canonical_record":{"source":{"id":"1210.1207","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2012-10-04T04:53:42Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"1f526697e87dffe59561478a9013df552749a99b9351d6e509923df08d2a10cf","abstract_canon_sha256":"c9dd992d365e14098b818e7821c2d94630c063534235fe37f8a5fde05278526f"},"schema_version":"1.0"},"canonical_sha256":"458b8c23767df80cb62da965ebac96d7def5afae4222ddb45aceec43a9762636","source":{"kind":"arxiv","id":"1210.1207","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1210.1207","created_at":"2026-05-18T03:26:32Z"},{"alias_kind":"arxiv_version","alias_value":"1210.1207v2","created_at":"2026-05-18T03:26:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1210.1207","created_at":"2026-05-18T03:26:32Z"},{"alias_kind":"pith_short_12","alias_value":"IWFYYI3WPX4A","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_16","alias_value":"IWFYYI3WPX4AZNRN","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_8","alias_value":"IWFYYI3W","created_at":"2026-05-18T12:27:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:IWFYYI3WPX4AZNRNVFS6XLEW27","target":"record","payload":{"canonical_record":{"source":{"id":"1210.1207","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2012-10-04T04:53:42Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"1f526697e87dffe59561478a9013df552749a99b9351d6e509923df08d2a10cf","abstract_canon_sha256":"c9dd992d365e14098b818e7821c2d94630c063534235fe37f8a5fde05278526f"},"schema_version":"1.0"},"canonical_sha256":"458b8c23767df80cb62da965ebac96d7def5afae4222ddb45aceec43a9762636","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:26:32.376021Z","signature_b64":"/m4SgK/rbhdrCXRDFpnKaRqutoXhao0mPTVj1XRB2knv39okiXVPUj8754UUETdreD9gpOFW4ClMFsxkJkG8DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"458b8c23767df80cb62da965ebac96d7def5afae4222ddb45aceec43a9762636","last_reissued_at":"2026-05-18T03:26:32.375567Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:26:32.375567Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1210.1207","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:26:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"960nx+KRe23f3wWBzX/5Wzyp+0Ax+Cs6pQGc34nr3AXhonHQbPOqwZ6rsy/dsbxUajwXLHflR+UVFEC+cIn/Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T14:42:06.177960Z"},"content_sha256":"764eb5e4cf8b253e91ee1529574bae06e53dc78c6ada15ebc769afc2dc7e1cdb","schema_version":"1.0","event_id":"sha256:764eb5e4cf8b253e91ee1529574bae06e53dc78c6ada15ebc769afc2dc7e1cdb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:IWFYYI3WPX4AZNRNVFS6XLEW27","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Human Activities and Object Affordances from RGB-D Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.RO","authors_text":"Ashutosh Saxena, Hema Swetha Koppula, Rudhir Gupta","submitted_at":"2012-10-04T04:53:42Z","abstract_excerpt":"Understanding human activities and object affordances are two very important skills, especially for personal robots which operate in human environments. In this work, we consider the problem of extracting a descriptive labeling of the sequence of sub-activities being performed by a human, and more importantly, of their interactions with the objects in the form of associated affordances. Given a RGB-D video, we jointly model the human activities and object affordances as a Markov random field where the nodes represent objects and sub-activities, and the edges represent the relationships between"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1210.1207","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:26:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p7AtnFZvHIFMUKiiJBxUT3PZ8FxUumkZ3TWHeouGrvoYDr5TbcmAmXGDHZ/4zCPKYVOGhZBQyskS/DW8MDbkAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T14:42:06.178333Z"},"content_sha256":"d1b46266def8a1536409a1674a2c71b727f2865274f67fc20c2757b76684ab9d","schema_version":"1.0","event_id":"sha256:d1b46266def8a1536409a1674a2c71b727f2865274f67fc20c2757b76684ab9d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IWFYYI3WPX4AZNRNVFS6XLEW27/bundle.json","state_url":"https://pith.science/pith/IWFYYI3WPX4AZNRNVFS6XLEW27/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IWFYYI3WPX4AZNRNVFS6XLEW27/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":"2026-05-26T14:42:06Z","links":{"resolver":"https://pith.science/pith/IWFYYI3WPX4AZNRNVFS6XLEW27","bundle":"https://pith.science/pith/IWFYYI3WPX4AZNRNVFS6XLEW27/bundle.json","state":"https://pith.science/pith/IWFYYI3WPX4AZNRNVFS6XLEW27/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IWFYYI3WPX4AZNRNVFS6XLEW27/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:IWFYYI3WPX4AZNRNVFS6XLEW27","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":"c9dd992d365e14098b818e7821c2d94630c063534235fe37f8a5fde05278526f","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2012-10-04T04:53:42Z","title_canon_sha256":"1f526697e87dffe59561478a9013df552749a99b9351d6e509923df08d2a10cf"},"schema_version":"1.0","source":{"id":"1210.1207","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1210.1207","created_at":"2026-05-18T03:26:32Z"},{"alias_kind":"arxiv_version","alias_value":"1210.1207v2","created_at":"2026-05-18T03:26:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1210.1207","created_at":"2026-05-18T03:26:32Z"},{"alias_kind":"pith_short_12","alias_value":"IWFYYI3WPX4A","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_16","alias_value":"IWFYYI3WPX4AZNRN","created_at":"2026-05-18T12:27:09Z"},{"alias_kind":"pith_short_8","alias_value":"IWFYYI3W","created_at":"2026-05-18T12:27:09Z"}],"graph_snapshots":[{"event_id":"sha256:d1b46266def8a1536409a1674a2c71b727f2865274f67fc20c2757b76684ab9d","target":"graph","created_at":"2026-05-18T03:26:32Z","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":"Understanding human activities and object affordances are two very important skills, especially for personal robots which operate in human environments. In this work, we consider the problem of extracting a descriptive labeling of the sequence of sub-activities being performed by a human, and more importantly, of their interactions with the objects in the form of associated affordances. Given a RGB-D video, we jointly model the human activities and object affordances as a Markov random field where the nodes represent objects and sub-activities, and the edges represent the relationships between","authors_text":"Ashutosh Saxena, Hema Swetha Koppula, Rudhir Gupta","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2012-10-04T04:53:42Z","title":"Learning Human Activities and Object Affordances from RGB-D Videos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1210.1207","kind":"arxiv","version":2},"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":"sha256:764eb5e4cf8b253e91ee1529574bae06e53dc78c6ada15ebc769afc2dc7e1cdb","target":"record","created_at":"2026-05-18T03:26:32Z","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":"c9dd992d365e14098b818e7821c2d94630c063534235fe37f8a5fde05278526f","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2012-10-04T04:53:42Z","title_canon_sha256":"1f526697e87dffe59561478a9013df552749a99b9351d6e509923df08d2a10cf"},"schema_version":"1.0","source":{"id":"1210.1207","kind":"arxiv","version":2}},"canonical_sha256":"458b8c23767df80cb62da965ebac96d7def5afae4222ddb45aceec43a9762636","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"458b8c23767df80cb62da965ebac96d7def5afae4222ddb45aceec43a9762636","first_computed_at":"2026-05-18T03:26:32.375567Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:26:32.375567Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/m4SgK/rbhdrCXRDFpnKaRqutoXhao0mPTVj1XRB2knv39okiXVPUj8754UUETdreD9gpOFW4ClMFsxkJkG8DA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:26:32.376021Z","signed_message":"canonical_sha256_bytes"},"source_id":"1210.1207","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:764eb5e4cf8b253e91ee1529574bae06e53dc78c6ada15ebc769afc2dc7e1cdb","sha256:d1b46266def8a1536409a1674a2c71b727f2865274f67fc20c2757b76684ab9d"],"state_sha256":"c5225f25fca4ff835f4d788b49b318253a44fb84c0b5e8702bace66729ae1adc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fkHZmV572l10Ubr9Grg6gfT4GplUlbww/+tmTK4aHfMwmVT1tsCSlgv7wtCXdOTXQ1Q2aqkxGgYClwzpAA9iAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T14:42:06.181129Z","bundle_sha256":"4125ec0f82b7baaae884eb3d501866a19167939c7e3bd4fca2db2bf91284f9cf"}}