{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:KMBJDCJ7RAIBRFKU7N3DKSZN37","short_pith_number":"pith:KMBJDCJ7","canonical_record":{"source":{"id":"1904.09843","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-19T14:32:40Z","cross_cats_sorted":[],"title_canon_sha256":"2bae4354ca0a41f0988f8151d0fbefb4bf962e033d0178aa02a2109c25a0dbc7","abstract_canon_sha256":"e2630bc0daa892c9702340d5efcf9869352cfe012adf8bacd5f4eaa4a3c1bce9"},"schema_version":"1.0"},"canonical_sha256":"530291893f8810189554fb76354b2ddfe4ce62d854a83e53384044cec4ff96ba","source":{"kind":"arxiv","id":"1904.09843","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.09843","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"arxiv_version","alias_value":"1904.09843v1","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.09843","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"pith_short_12","alias_value":"KMBJDCJ7RAIB","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KMBJDCJ7RAIBRFKU","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KMBJDCJ7","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:KMBJDCJ7RAIBRFKU7N3DKSZN37","target":"record","payload":{"canonical_record":{"source":{"id":"1904.09843","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-19T14:32:40Z","cross_cats_sorted":[],"title_canon_sha256":"2bae4354ca0a41f0988f8151d0fbefb4bf962e033d0178aa02a2109c25a0dbc7","abstract_canon_sha256":"e2630bc0daa892c9702340d5efcf9869352cfe012adf8bacd5f4eaa4a3c1bce9"},"schema_version":"1.0"},"canonical_sha256":"530291893f8810189554fb76354b2ddfe4ce62d854a83e53384044cec4ff96ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:03.106214Z","signature_b64":"1l4vDnOH62liI/aH7PSOvoa5IsjuWMhKts3IhMILdhJ48ORoo5VMyES2QnaIFEIh9TPz4WQ4I2vXThCBZepGBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"530291893f8810189554fb76354b2ddfe4ce62d854a83e53384044cec4ff96ba","last_reissued_at":"2026-05-17T23:48:03.105529Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:03.105529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.09843","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":"2026-05-17T23:48:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Na69cfS/L0Y4Muhw4V8iK+51MBOJkOcY8sXi30ZhhSHim2Qz3uCN9cTXfkD05LRBXlurHv347XaLa38BrcMoBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T22:08:17.612062Z"},"content_sha256":"acbcd2d8235e259a1e9517194a6b90967994156068b4541c394eb6d153f6da07","schema_version":"1.0","event_id":"sha256:acbcd2d8235e259a1e9517194a6b90967994156068b4541c394eb6d153f6da07"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:KMBJDCJ7RAIBRFKU7N3DKSZN37","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GestARLite: An On-Device Pointing Finger Based Gestural Interface for Smartphones and Video See-Through Head-Mounts","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Gaurav Garg, Ramakrishna Perla, Ramya Hebbalaguppe, Varun Jain","submitted_at":"2019-04-19T14:32:40Z","abstract_excerpt":"Hand gestures form an intuitive means of interaction in Mixed Reality (MR) applications. However, accurate gesture recognition can be achieved only through state-of-the-art deep learning models or with the use of expensive sensors. Despite the robustness of these deep learning models, they are generally computationally expensive and obtaining real-time performance on-device is still a challenge. To this end, we propose a novel lightweight hand gesture recognition framework that works in First Person View for wearable devices. The models are trained on a GPU machine and ported on an Android sma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.09843","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":"2026-05-17T23:48:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lUQCgthMILETWQVn20DFtTS5D7jjvbZSRoUtEzeOJ7pGb7kmBQo8FlM5SyFrzSfEGynq1bnPNHOn4Cyc3LraAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T22:08:17.612784Z"},"content_sha256":"308e171490ac81cae586f6722c6c2e077941719d329ccac0358134c24e4cc6ba","schema_version":"1.0","event_id":"sha256:308e171490ac81cae586f6722c6c2e077941719d329ccac0358134c24e4cc6ba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KMBJDCJ7RAIBRFKU7N3DKSZN37/bundle.json","state_url":"https://pith.science/pith/KMBJDCJ7RAIBRFKU7N3DKSZN37/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KMBJDCJ7RAIBRFKU7N3DKSZN37/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":"2026-06-05T22:08:17Z","links":{"resolver":"https://pith.science/pith/KMBJDCJ7RAIBRFKU7N3DKSZN37","bundle":"https://pith.science/pith/KMBJDCJ7RAIBRFKU7N3DKSZN37/bundle.json","state":"https://pith.science/pith/KMBJDCJ7RAIBRFKU7N3DKSZN37/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KMBJDCJ7RAIBRFKU7N3DKSZN37/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:KMBJDCJ7RAIBRFKU7N3DKSZN37","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":"e2630bc0daa892c9702340d5efcf9869352cfe012adf8bacd5f4eaa4a3c1bce9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-19T14:32:40Z","title_canon_sha256":"2bae4354ca0a41f0988f8151d0fbefb4bf962e033d0178aa02a2109c25a0dbc7"},"schema_version":"1.0","source":{"id":"1904.09843","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.09843","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"arxiv_version","alias_value":"1904.09843v1","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.09843","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"pith_short_12","alias_value":"KMBJDCJ7RAIB","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KMBJDCJ7RAIBRFKU","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KMBJDCJ7","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:308e171490ac81cae586f6722c6c2e077941719d329ccac0358134c24e4cc6ba","target":"graph","created_at":"2026-05-17T23:48:03Z","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":"Hand gestures form an intuitive means of interaction in Mixed Reality (MR) applications. However, accurate gesture recognition can be achieved only through state-of-the-art deep learning models or with the use of expensive sensors. Despite the robustness of these deep learning models, they are generally computationally expensive and obtaining real-time performance on-device is still a challenge. To this end, we propose a novel lightweight hand gesture recognition framework that works in First Person View for wearable devices. The models are trained on a GPU machine and ported on an Android sma","authors_text":"Gaurav Garg, Ramakrishna Perla, Ramya Hebbalaguppe, Varun Jain","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-19T14:32:40Z","title":"GestARLite: An On-Device Pointing Finger Based Gestural Interface for Smartphones and Video See-Through Head-Mounts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.09843","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:acbcd2d8235e259a1e9517194a6b90967994156068b4541c394eb6d153f6da07","target":"record","created_at":"2026-05-17T23:48:03Z","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":"e2630bc0daa892c9702340d5efcf9869352cfe012adf8bacd5f4eaa4a3c1bce9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-19T14:32:40Z","title_canon_sha256":"2bae4354ca0a41f0988f8151d0fbefb4bf962e033d0178aa02a2109c25a0dbc7"},"schema_version":"1.0","source":{"id":"1904.09843","kind":"arxiv","version":1}},"canonical_sha256":"530291893f8810189554fb76354b2ddfe4ce62d854a83e53384044cec4ff96ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"530291893f8810189554fb76354b2ddfe4ce62d854a83e53384044cec4ff96ba","first_computed_at":"2026-05-17T23:48:03.105529Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:03.105529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1l4vDnOH62liI/aH7PSOvoa5IsjuWMhKts3IhMILdhJ48ORoo5VMyES2QnaIFEIh9TPz4WQ4I2vXThCBZepGBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:03.106214Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.09843","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:acbcd2d8235e259a1e9517194a6b90967994156068b4541c394eb6d153f6da07","sha256:308e171490ac81cae586f6722c6c2e077941719d329ccac0358134c24e4cc6ba"],"state_sha256":"01f187b4d761854afdc2dd0ef37b91823fcebe52d2d5bfe63382e459ba611975"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r9Exrz5afcD2IGdGS8pyzSFbWIhXtssGlfUlfj1QsyqdMRYh6TWw1Qd5k+7zSxB5/i1h51b3DMwMCjJ+mu1CDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T22:08:17.616606Z","bundle_sha256":"5457703fb81fdc1afeb22ff8c38634eb592665dd87d8378e1966caa5099cf65d"}}