{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:RU2LTML4VGCOUMUE5POBNPWARS","short_pith_number":"pith:RU2LTML4","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"},"canonical_sha256":"8d34b9b17ca984ea3284ebdc16bec08c9b6e4254c0a7342ecd8ad31eb0541950","source":{"kind":"arxiv","id":"1607.04441","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.04441","created_at":"2026-05-17T23:58:23Z"},{"alias_kind":"arxiv_version","alias_value":"1607.04441v3","created_at":"2026-05-17T23:58:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.04441","created_at":"2026-05-17T23:58:23Z"},{"alias_kind":"pith_short_12","alias_value":"RU2LTML4VGCO","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"RU2LTML4VGCOUMUE","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"RU2LTML4","created_at":"2026-05-18T12:30:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:RU2LTML4VGCOUMUE5POBNPWARS","target":"record","payload":{"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"},"canonical_sha256":"8d34b9b17ca984ea3284ebdc16bec08c9b6e4254c0a7342ecd8ad31eb0541950","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"},"source_kind":"arxiv","source_id":"1607.04441","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:58:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OP+qtL15P6AON0WiQ7lmfE3L7rzNCVElJevcv21hgsoDTnePGSR4euFvAHIhFPQTwQymUtVPwl0MH6JrLMqzDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T18:08:48.405518Z"},"content_sha256":"326248c4e87c18890657bb3d951136a09089505846f605c4262f52b27cf941ab","schema_version":"1.0","event_id":"sha256:326248c4e87c18890657bb3d951136a09089505846f605c4262f52b27cf941ab"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:RU2LTML4VGCOUMUE5POBNPWARS","target":"graph","payload":{"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:58:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4kvku6v3rPNnfD9Q2sQmt0wke+OwJJKjOVtT0ihz4Cy1ssg8J/WKmxx0FAMnNV1NqeykP77KggwI+NEH+a5FCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T18:08:48.405857Z"},"content_sha256":"eacb68383c7bae50a3bf00dfa96a45314fe6c19aabb141a0f636975d05420e09","schema_version":"1.0","event_id":"sha256:eacb68383c7bae50a3bf00dfa96a45314fe6c19aabb141a0f636975d05420e09"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/bundle.json","state_url":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RU2LTML4VGCOUMUE5POBNPWARS/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":"2026-06-27T18:08:48Z","links":{"resolver":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS","bundle":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/bundle.json","state":"https://pith.science/pith/RU2LTML4VGCOUMUE5POBNPWARS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RU2LTML4VGCOUMUE5POBNPWARS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:RU2LTML4VGCOUMUE5POBNPWARS","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":"2d2e7e5037894e29b9548b03d3d3badba9064d3c3fcda6bcfde27ccd719d7f45","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-15T10:16:45Z","title_canon_sha256":"2adc3a0834a6b13ca19fc3d0d7f36be7bd2170e243a8eeb23b293107e66076d2"},"schema_version":"1.0","source":{"id":"1607.04441","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.04441","created_at":"2026-05-17T23:58:23Z"},{"alias_kind":"arxiv_version","alias_value":"1607.04441v3","created_at":"2026-05-17T23:58:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.04441","created_at":"2026-05-17T23:58:23Z"},{"alias_kind":"pith_short_12","alias_value":"RU2LTML4VGCO","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"RU2LTML4VGCOUMUE","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"RU2LTML4","created_at":"2026-05-18T12:30:41Z"}],"graph_snapshots":[{"event_id":"sha256:eacb68383c7bae50a3bf00dfa96a45314fe6c19aabb141a0f636975d05420e09","target":"graph","created_at":"2026-05-17T23:58:23Z","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":"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'","authors_text":"Andre Mateus, David Ribeiro, Jacinto C. Nascimento, Pedro Miraldo","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-15T10:16:45Z","title":"Efficient and Robust Pedestrian Detection using Deep Learning for Human-Aware Navigation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.04441","kind":"arxiv","version":3},"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":"sha256:326248c4e87c18890657bb3d951136a09089505846f605c4262f52b27cf941ab","target":"record","created_at":"2026-05-17T23:58:23Z","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":"2d2e7e5037894e29b9548b03d3d3badba9064d3c3fcda6bcfde27ccd719d7f45","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-15T10:16:45Z","title_canon_sha256":"2adc3a0834a6b13ca19fc3d0d7f36be7bd2170e243a8eeb23b293107e66076d2"},"schema_version":"1.0","source":{"id":"1607.04441","kind":"arxiv","version":3}},"canonical_sha256":"8d34b9b17ca984ea3284ebdc16bec08c9b6e4254c0a7342ecd8ad31eb0541950","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8d34b9b17ca984ea3284ebdc16bec08c9b6e4254c0a7342ecd8ad31eb0541950","first_computed_at":"2026-05-17T23:58:23.385137Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:58:23.385137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"E79t8T3UTlF2ubd9iPkXx6OvN3DXzCLirdmpNRu26nyNWSGiqbTC33pr86jLEHKAGcUO03QoPr4aigeHcO27DQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:58:23.385836Z","signed_message":"canonical_sha256_bytes"},"source_id":"1607.04441","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:326248c4e87c18890657bb3d951136a09089505846f605c4262f52b27cf941ab","sha256:eacb68383c7bae50a3bf00dfa96a45314fe6c19aabb141a0f636975d05420e09"],"state_sha256":"4ca8862d1716d9593b101e4151377e7caf5a08324e6b68402fed33db28805d80"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m/BHNopz7NO0YtVLgX4DhYC3kh/hfKRL31jAEC5np3Lfr2KINmSSXP5BgsW4AXOz4o/DIjtUAGglYGuLpwKUAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T18:08:48.407694Z","bundle_sha256":"23d58df0e08749dc3ce735652bbc9d667678b4b70d2929fae52bf3f07973cfa7"}}