{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:RWO7DZCZC4M2P5MEDXOIG2KTH4","short_pith_number":"pith:RWO7DZCZ","schema_version":"1.0","canonical_sha256":"8d9df1e4591719a7f5841ddc8369533f14932fc6b6feb3c8f7f6f0edc8b48f1d","source":{"kind":"arxiv","id":"1908.02635","version":1},"attestation_state":"computed","paper":{"title":"Mono-Stixels: Monocular depth reconstruction of dynamic street scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fabian Brickwedde, Rudolf Mester, Steffen Abraham","submitted_at":"2019-08-07T13:54:51Z","abstract_excerpt":"In this paper we present mono-stixels, a compact environment representation specially designed for dynamic street scenes. Mono-stixels are a novel approach to estimate stixels from a monocular camera sequence instead of the traditionally used stereo depth measurements. Our approach jointly infers the depth, motion and semantic information of the dynamic scene as a 1D energy minimization problem based on optical flow estimates, pixel-wise semantic segmentation and camera motion. The optical flow of a stixel is described by a homography. By applying the mono-stixel model the degrees of freedom o"},"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":"1908.02635","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-07T13:54:51Z","cross_cats_sorted":[],"title_canon_sha256":"307c5f8efffa9760de5a00cfd3b2ad3f88e2048b18e328807394cc1c8e7f2df1","abstract_canon_sha256":"39aaef627fab08b4a13312a35ac0a4b17c3c55e94a775d4421388dded20c2f25"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:52:11.026626Z","signature_b64":"BY2OHU3WUgdW+lM5mkz9UDDoyMbtcljr8AWiUGGhaKc59Z0Cp6ieYzMaGjUmkUtAr2tIYjKOIL6Clcbq1KtfAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8d9df1e4591719a7f5841ddc8369533f14932fc6b6feb3c8f7f6f0edc8b48f1d","last_reissued_at":"2026-07-04T23:52:11.026157Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:52:11.026157Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Mono-Stixels: Monocular depth reconstruction of dynamic street scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fabian Brickwedde, Rudolf Mester, Steffen Abraham","submitted_at":"2019-08-07T13:54:51Z","abstract_excerpt":"In this paper we present mono-stixels, a compact environment representation specially designed for dynamic street scenes. Mono-stixels are a novel approach to estimate stixels from a monocular camera sequence instead of the traditionally used stereo depth measurements. Our approach jointly infers the depth, motion and semantic information of the dynamic scene as a 1D energy minimization problem based on optical flow estimates, pixel-wise semantic segmentation and camera motion. The optical flow of a stixel is described by a homography. By applying the mono-stixel model the degrees of freedom o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.02635","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.02635/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"1908.02635","created_at":"2026-07-04T23:52:11.026214+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.02635v1","created_at":"2026-07-04T23:52:11.026214+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.02635","created_at":"2026-07-04T23:52:11.026214+00:00"},{"alias_kind":"pith_short_12","alias_value":"RWO7DZCZC4M2","created_at":"2026-07-04T23:52:11.026214+00:00"},{"alias_kind":"pith_short_16","alias_value":"RWO7DZCZC4M2P5ME","created_at":"2026-07-04T23:52:11.026214+00:00"},{"alias_kind":"pith_short_8","alias_value":"RWO7DZCZ","created_at":"2026-07-04T23:52:11.026214+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.06687","citing_title":"StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception","ref_index":9,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4","json":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4.json","graph_json":"https://pith.science/api/pith-number/RWO7DZCZC4M2P5MEDXOIG2KTH4/graph.json","events_json":"https://pith.science/api/pith-number/RWO7DZCZC4M2P5MEDXOIG2KTH4/events.json","paper":"https://pith.science/paper/RWO7DZCZ"},"agent_actions":{"view_html":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4","download_json":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4.json","view_paper":"https://pith.science/paper/RWO7DZCZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.02635&json=true","fetch_graph":"https://pith.science/api/pith-number/RWO7DZCZC4M2P5MEDXOIG2KTH4/graph.json","fetch_events":"https://pith.science/api/pith-number/RWO7DZCZC4M2P5MEDXOIG2KTH4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4/action/storage_attestation","attest_author":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4/action/author_attestation","sign_citation":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4/action/citation_signature","submit_replication":"https://pith.science/pith/RWO7DZCZC4M2P5MEDXOIG2KTH4/action/replication_record"}},"created_at":"2026-07-04T23:52:11.026214+00:00","updated_at":"2026-07-04T23:52:11.026214+00:00"}