{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:Y3TKSR2EST2F7R5WXZ4FT56HB6","short_pith_number":"pith:Y3TKSR2E","canonical_record":{"source":{"id":"1711.10143","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-28T06:38:02Z","cross_cats_sorted":[],"title_canon_sha256":"e2c1f7ccfe887a222e1e8b369eb621c5b0c7b095f027bf1f6282b5e4db986d18","abstract_canon_sha256":"f64a96ebe5a08d160958cd35f52ac780ede0039db08df8feea6486ce214a0414"},"schema_version":"1.0"},"canonical_sha256":"c6e6a9474494f45fc7b6be7859f7c70faefec9eca45f6faa8a5cb5f0872581ce","source":{"kind":"arxiv","id":"1711.10143","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.10143","created_at":"2026-05-18T00:29:23Z"},{"alias_kind":"arxiv_version","alias_value":"1711.10143v1","created_at":"2026-05-18T00:29:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.10143","created_at":"2026-05-18T00:29:23Z"},{"alias_kind":"pith_short_12","alias_value":"Y3TKSR2EST2F","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"Y3TKSR2EST2F7R5W","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"Y3TKSR2E","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:Y3TKSR2EST2F7R5WXZ4FT56HB6","target":"record","payload":{"canonical_record":{"source":{"id":"1711.10143","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-28T06:38:02Z","cross_cats_sorted":[],"title_canon_sha256":"e2c1f7ccfe887a222e1e8b369eb621c5b0c7b095f027bf1f6282b5e4db986d18","abstract_canon_sha256":"f64a96ebe5a08d160958cd35f52ac780ede0039db08df8feea6486ce214a0414"},"schema_version":"1.0"},"canonical_sha256":"c6e6a9474494f45fc7b6be7859f7c70faefec9eca45f6faa8a5cb5f0872581ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:23.242784Z","signature_b64":"FWHvZuvouPndw1R+wlIh51H5s4b7VS8paryp3Qd8Acg5tbfQ75efd6dIZqzq7deY+m/v8FHNXoJ9Xe1HXzArCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c6e6a9474494f45fc7b6be7859f7c70faefec9eca45f6faa8a5cb5f0872581ce","last_reissued_at":"2026-05-18T00:29:23.242038Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:23.242038Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.10143","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":"2026-05-18T00:29:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qOGkbQphYRSRFwQMlCYNyhciMciSGDw0aTw4aLQVGJooR3vfw7DAsGP9NQjPPDagS3rpcex2lJ1KrDJvBuN2Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T08:36:27.281695Z"},"content_sha256":"a0b81ae9fbbf18f45878bc281f20aa52fc289cdc9c33d2b438e29ac4ec2dd0a2","schema_version":"1.0","event_id":"sha256:a0b81ae9fbbf18f45878bc281f20aa52fc289cdc9c33d2b438e29ac4ec2dd0a2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:Y3TKSR2EST2F7R5WXZ4FT56HB6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting hand-crafted feature for action recognition: a set of improved dense trajectories","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bisser Raytchev, Gwladys Auffret, Kazufumi Kaneda, Kenji Matsui, Toru Tamaki","submitted_at":"2017-11-28T06:38:02Z","abstract_excerpt":"We propose a feature for action recognition called Trajectory-Set (TS), on top of the improved Dense Trajectory (iDT). The TS feature encodes only trajectories around densely sampled interest points, without any appearance features. Experimental results on the UCF50, UCF101, and HMDB51 action datasets demonstrate that TS is comparable to state-of-the-arts, and outperforms many other methods; for HMDB the accuracy of 85.4%, compared to the best accuracy of 80.2% obtained by a deep method. Our code is available on-line at https://github.com/Gauffret/TrajectorySet ."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.10143","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":"2026-05-18T00:29:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QXRF02Q4aAYx5cRs26E+h5gT8rBxrzB1BDKLmcUZNjEP96XQ9tP2IZGEmwhMFtVm83eNi/l2ysp+9QAex6YLAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T08:36:27.282032Z"},"content_sha256":"91012842ba9c0121193f0514f0bb01b138efa84472999048782ed2910602e9ef","schema_version":"1.0","event_id":"sha256:91012842ba9c0121193f0514f0bb01b138efa84472999048782ed2910602e9ef"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y3TKSR2EST2F7R5WXZ4FT56HB6/bundle.json","state_url":"https://pith.science/pith/Y3TKSR2EST2F7R5WXZ4FT56HB6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y3TKSR2EST2F7R5WXZ4FT56HB6/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":"2026-06-03T08:36:27Z","links":{"resolver":"https://pith.science/pith/Y3TKSR2EST2F7R5WXZ4FT56HB6","bundle":"https://pith.science/pith/Y3TKSR2EST2F7R5WXZ4FT56HB6/bundle.json","state":"https://pith.science/pith/Y3TKSR2EST2F7R5WXZ4FT56HB6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y3TKSR2EST2F7R5WXZ4FT56HB6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:Y3TKSR2EST2F7R5WXZ4FT56HB6","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":"f64a96ebe5a08d160958cd35f52ac780ede0039db08df8feea6486ce214a0414","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-28T06:38:02Z","title_canon_sha256":"e2c1f7ccfe887a222e1e8b369eb621c5b0c7b095f027bf1f6282b5e4db986d18"},"schema_version":"1.0","source":{"id":"1711.10143","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.10143","created_at":"2026-05-18T00:29:23Z"},{"alias_kind":"arxiv_version","alias_value":"1711.10143v1","created_at":"2026-05-18T00:29:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.10143","created_at":"2026-05-18T00:29:23Z"},{"alias_kind":"pith_short_12","alias_value":"Y3TKSR2EST2F","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"Y3TKSR2EST2F7R5W","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"Y3TKSR2E","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:91012842ba9c0121193f0514f0bb01b138efa84472999048782ed2910602e9ef","target":"graph","created_at":"2026-05-18T00:29:23Z","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 a feature for action recognition called Trajectory-Set (TS), on top of the improved Dense Trajectory (iDT). The TS feature encodes only trajectories around densely sampled interest points, without any appearance features. Experimental results on the UCF50, UCF101, and HMDB51 action datasets demonstrate that TS is comparable to state-of-the-arts, and outperforms many other methods; for HMDB the accuracy of 85.4%, compared to the best accuracy of 80.2% obtained by a deep method. Our code is available on-line at https://github.com/Gauffret/TrajectorySet .","authors_text":"Bisser Raytchev, Gwladys Auffret, Kazufumi Kaneda, Kenji Matsui, Toru Tamaki","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-28T06:38:02Z","title":"Revisiting hand-crafted feature for action recognition: a set of improved dense trajectories"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.10143","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:a0b81ae9fbbf18f45878bc281f20aa52fc289cdc9c33d2b438e29ac4ec2dd0a2","target":"record","created_at":"2026-05-18T00:29:23Z","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":"f64a96ebe5a08d160958cd35f52ac780ede0039db08df8feea6486ce214a0414","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-28T06:38:02Z","title_canon_sha256":"e2c1f7ccfe887a222e1e8b369eb621c5b0c7b095f027bf1f6282b5e4db986d18"},"schema_version":"1.0","source":{"id":"1711.10143","kind":"arxiv","version":1}},"canonical_sha256":"c6e6a9474494f45fc7b6be7859f7c70faefec9eca45f6faa8a5cb5f0872581ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c6e6a9474494f45fc7b6be7859f7c70faefec9eca45f6faa8a5cb5f0872581ce","first_computed_at":"2026-05-18T00:29:23.242038Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:23.242038Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FWHvZuvouPndw1R+wlIh51H5s4b7VS8paryp3Qd8Acg5tbfQ75efd6dIZqzq7deY+m/v8FHNXoJ9Xe1HXzArCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:23.242784Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.10143","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0b81ae9fbbf18f45878bc281f20aa52fc289cdc9c33d2b438e29ac4ec2dd0a2","sha256:91012842ba9c0121193f0514f0bb01b138efa84472999048782ed2910602e9ef"],"state_sha256":"eaca7afc1f630aec6b46d99829eec4effefcef64896d93a9a7954b208223f1c0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g0kcC7ksSahRjwOVbQXCLfcDrSI40XdcvIlnuZe787T2xjyl37l1N6YaEeGt09cgHRvXaSb+R6VeJPCajdeUBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T08:36:27.283948Z","bundle_sha256":"d603b1726d5c2c555a9307a2aba27c74d10798dc5230776ac951aaf9a48967eb"}}