{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:RU2LTML4VGCOUMUE5POBNPWARS","short_pith_number":"pith:RU2LTML4","schema_version":"1.0","canonical_sha256":"8d34b9b17ca984ea3284ebdc16bec08c9b6e4254c0a7342ecd8ad31eb0541950","source":{"kind":"arxiv","id":"1607.04441","version":3},"attestation_state":"computed","paper":{"title":"Efficient and Robust Pedestrian Detection using Deep Learning for Human-Aware Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Andre Mateus, David Ribeiro, Jacinto C. Nascimento, Pedro Miraldo","submitted_at":"2016-07-15T10:16:45Z","abstract_excerpt":"This paper addresses the problem of Human-Aware Navigation (HAN), using multi camera sensors to implement a vision-based person tracking system. The main contributions of this paper are as follows: a novel and efficient Deep Learning person detection and a standardization of human-aware constraints. In the first stage of the approach, we propose to cascade the Aggregate Channel Features (ACF) detector with a deep Convolutional Neural Network (CNN) to achieve fast and accurate Pedestrian Detection (PD). Regarding the human awareness (that can be defined as constraints associated with the robot'"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1607.04441","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-15T10:16:45Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2adc3a0834a6b13ca19fc3d0d7f36be7bd2170e243a8eeb23b293107e66076d2","abstract_canon_sha256":"2d2e7e5037894e29b9548b03d3d3badba9064d3c3fcda6bcfde27ccd719d7f45"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:58:23.385836Z","signature_b64":"E79t8T3UTlF2ubd9iPkXx6OvN3DXzCLirdmpNRu26nyNWSGiqbTC33pr86jLEHKAGcUO03QoPr4aigeHcO27DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8d34b9b17ca984ea3284ebdc16bec08c9b6e4254c0a7342ecd8ad31eb0541950","last_reissued_at":"2026-05-17T23:58:23.385137Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:58:23.385137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient and Robust Pedestrian Detection using Deep Learning for Human-Aware Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Andre Mateus, David Ribeiro, Jacinto C. Nascimento, Pedro Miraldo","submitted_at":"2016-07-15T10:16:45Z","abstract_excerpt":"This paper addresses the problem of Human-Aware Navigation (HAN), using multi camera sensors to implement a vision-based person tracking system. The main contributions of this paper are as follows: a novel and efficient Deep Learning person detection and a standardization of human-aware constraints. In the first stage of the approach, we propose to cascade the Aggregate Channel Features (ACF) detector with a deep Convolutional Neural Network (CNN) to achieve fast and accurate Pedestrian Detection (PD). Regarding the human awareness (that can be defined as constraints associated with the robot'"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.04441","kind":"arxiv","version":3},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1607.04441","created_at":"2026-05-17T23:58:23.385233+00:00"},{"alias_kind":"arxiv_version","alias_value":"1607.04441v3","created_at":"2026-05-17T23:58:23.385233+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.04441","created_at":"2026-05-17T23:58:23.385233+00:00"},{"alias_kind":"pith_short_12","alias_value":"RU2LTML4VGCO","created_at":"2026-05-18T12:30:41.710351+00:00"},{"alias_kind":"pith_short_16","alias_value":"RU2LTML4VGCOUMUE","created_at":"2026-05-18T12:30:41.710351+00:00"},{"alias_kind":"pith_short_8","alias_value":"RU2LTML4","created_at":"2026-05-18T12:30:41.710351+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS","json":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS.json","graph_json":"https://pith.science/api/pith-number/RU2LTML4VGCOUMUE5POBNPWARS/graph.json","events_json":"https://pith.science/api/pith-number/RU2LTML4VGCOUMUE5POBNPWARS/events.json","paper":"https://pith.science/paper/RU2LTML4"},"agent_actions":{"view_html":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS","download_json":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS.json","view_paper":"https://pith.science/paper/RU2LTML4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1607.04441&json=true","fetch_graph":"https://pith.science/api/pith-number/RU2LTML4VGCOUMUE5POBNPWARS/graph.json","fetch_events":"https://pith.science/api/pith-number/RU2LTML4VGCOUMUE5POBNPWARS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/action/storage_attestation","attest_author":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/action/author_attestation","sign_citation":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/action/citation_signature","submit_replication":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/action/replication_record"}},"created_at":"2026-05-17T23:58:23.385233+00:00","updated_at":"2026-05-17T23:58:23.385233+00:00"}