{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:N4ST3K6GDBUI2MAT4AEVOZQKU4","short_pith_number":"pith:N4ST3K6G","canonical_record":{"source":{"id":"1806.06178","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-16T04:31:59Z","cross_cats_sorted":[],"title_canon_sha256":"9fc56db4a5cae18aaac304eac0d26eba156a1713f8a27d25b9fd88e0967e4de3","abstract_canon_sha256":"47da8b568286072d226ee04397c974f41da4fa9554a397d6537f551194280473"},"schema_version":"1.0"},"canonical_sha256":"6f253dabc618688d3013e00957660aa72f3bc936fcb8c0b0c120ac0569d5aae9","source":{"kind":"arxiv","id":"1806.06178","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.06178","created_at":"2026-05-18T00:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"1806.06178v1","created_at":"2026-05-18T00:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.06178","created_at":"2026-05-18T00:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"N4ST3K6GDBUI","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"N4ST3K6GDBUI2MAT","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"N4ST3K6G","created_at":"2026-05-18T12:32:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:N4ST3K6GDBUI2MAT4AEVOZQKU4","target":"record","payload":{"canonical_record":{"source":{"id":"1806.06178","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-16T04:31:59Z","cross_cats_sorted":[],"title_canon_sha256":"9fc56db4a5cae18aaac304eac0d26eba156a1713f8a27d25b9fd88e0967e4de3","abstract_canon_sha256":"47da8b568286072d226ee04397c974f41da4fa9554a397d6537f551194280473"},"schema_version":"1.0"},"canonical_sha256":"6f253dabc618688d3013e00957660aa72f3bc936fcb8c0b0c120ac0569d5aae9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:25.416938Z","signature_b64":"J0zX/KkMPKnEdYF3rmwgTvYf/q++wvcNSRLZ6+ggGA3LaoBwCjRGftCsKqWzIdqe2aBJrA5w7IMQyD9TSYj6Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f253dabc618688d3013e00957660aa72f3bc936fcb8c0b0c120ac0569d5aae9","last_reissued_at":"2026-05-18T00:08:25.416529Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:25.416529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.06178","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":"2026-05-18T00:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9C+n06LNSB8j8wQBA1Dpf2ciuxRBwr6OIoeCmI0K7IVRjPjYju+JhDrBaj3j+HWkhG8ZlbI40JLt8uU933WdAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:24:04.891492Z"},"content_sha256":"68cf5fb5e0bdd27846ed9e8af477b387b20bbfca9c28a2936b41193c7a781ad8","schema_version":"1.0","event_id":"sha256:68cf5fb5e0bdd27846ed9e8af477b387b20bbfca9c28a2936b41193c7a781ad8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:N4ST3K6GDBUI2MAT4AEVOZQKU4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Component SPD Matrices: A lower-dimensional discriminative data descriptor for image set classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kai-Xuan Chen, Xiao-Jun Wu","submitted_at":"2018-06-16T04:31:59Z","abstract_excerpt":"In the domain of pattern recognition, using the SPD (Symmetric Positive Definite) matrices to represent data and taking the metrics of resulting Riemannian manifold into account have been widely used for the task of image set classification. In this paper, we propose a new data representation framework for image sets named CSPD (Component Symmetric Positive Definite). Firstly, we obtain sub-image sets by dividing the image set into square blocks with the same size, and use traditional SPD model to describe them. Then, we use the results of the Riemannian kernel on SPD matrices as similarities "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.06178","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":"2026-05-18T00:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iFwO+QppJn+3JRhvGtI7zNmUVJQcBUY5eGGWCmn7eawPQKgywyH+73qEy9FAq9AcG/EOcOapTYKtfyFHs6ITAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:24:04.892152Z"},"content_sha256":"df49f46240753934503382b148f91e8e5241af276d28b2061a5fb9c329a835bb","schema_version":"1.0","event_id":"sha256:df49f46240753934503382b148f91e8e5241af276d28b2061a5fb9c329a835bb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N4ST3K6GDBUI2MAT4AEVOZQKU4/bundle.json","state_url":"https://pith.science/pith/N4ST3K6GDBUI2MAT4AEVOZQKU4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N4ST3K6GDBUI2MAT4AEVOZQKU4/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":"2026-05-30T08:24:04Z","links":{"resolver":"https://pith.science/pith/N4ST3K6GDBUI2MAT4AEVOZQKU4","bundle":"https://pith.science/pith/N4ST3K6GDBUI2MAT4AEVOZQKU4/bundle.json","state":"https://pith.science/pith/N4ST3K6GDBUI2MAT4AEVOZQKU4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N4ST3K6GDBUI2MAT4AEVOZQKU4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:N4ST3K6GDBUI2MAT4AEVOZQKU4","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":"47da8b568286072d226ee04397c974f41da4fa9554a397d6537f551194280473","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-16T04:31:59Z","title_canon_sha256":"9fc56db4a5cae18aaac304eac0d26eba156a1713f8a27d25b9fd88e0967e4de3"},"schema_version":"1.0","source":{"id":"1806.06178","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.06178","created_at":"2026-05-18T00:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"1806.06178v1","created_at":"2026-05-18T00:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.06178","created_at":"2026-05-18T00:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"N4ST3K6GDBUI","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"N4ST3K6GDBUI2MAT","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"N4ST3K6G","created_at":"2026-05-18T12:32:40Z"}],"graph_snapshots":[{"event_id":"sha256:df49f46240753934503382b148f91e8e5241af276d28b2061a5fb9c329a835bb","target":"graph","created_at":"2026-05-18T00:08:25Z","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 the domain of pattern recognition, using the SPD (Symmetric Positive Definite) matrices to represent data and taking the metrics of resulting Riemannian manifold into account have been widely used for the task of image set classification. In this paper, we propose a new data representation framework for image sets named CSPD (Component Symmetric Positive Definite). Firstly, we obtain sub-image sets by dividing the image set into square blocks with the same size, and use traditional SPD model to describe them. Then, we use the results of the Riemannian kernel on SPD matrices as similarities ","authors_text":"Kai-Xuan Chen, Xiao-Jun Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-16T04:31:59Z","title":"Component SPD Matrices: A lower-dimensional discriminative data descriptor for image set classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.06178","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":"sha256:68cf5fb5e0bdd27846ed9e8af477b387b20bbfca9c28a2936b41193c7a781ad8","target":"record","created_at":"2026-05-18T00:08:25Z","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":"47da8b568286072d226ee04397c974f41da4fa9554a397d6537f551194280473","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-16T04:31:59Z","title_canon_sha256":"9fc56db4a5cae18aaac304eac0d26eba156a1713f8a27d25b9fd88e0967e4de3"},"schema_version":"1.0","source":{"id":"1806.06178","kind":"arxiv","version":1}},"canonical_sha256":"6f253dabc618688d3013e00957660aa72f3bc936fcb8c0b0c120ac0569d5aae9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6f253dabc618688d3013e00957660aa72f3bc936fcb8c0b0c120ac0569d5aae9","first_computed_at":"2026-05-18T00:08:25.416529Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:08:25.416529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"J0zX/KkMPKnEdYF3rmwgTvYf/q++wvcNSRLZ6+ggGA3LaoBwCjRGftCsKqWzIdqe2aBJrA5w7IMQyD9TSYj6Ag==","signature_status":"signed_v1","signed_at":"2026-05-18T00:08:25.416938Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.06178","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68cf5fb5e0bdd27846ed9e8af477b387b20bbfca9c28a2936b41193c7a781ad8","sha256:df49f46240753934503382b148f91e8e5241af276d28b2061a5fb9c329a835bb"],"state_sha256":"adfd633b26007477f14a389889a0d7692ce6e919d29582b573b63c90dde0a32e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uJpQCzn1ALQuH3beYC1vnsilX0agJVl6+iy9X8/t3Xi2ARvkoo2X3LT2/tXgX2J0jnJ9/X77SO6vDWGXseVkBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T08:24:04.895073Z","bundle_sha256":"deba28247930b8e844830ef7631e98ee14e38d111d81d1248602d82594c816e1"}}