paper-with-me

홈 › Papers

Equivalence of Two Expressions of Principal Line

2023-01-08 · Cheng-Yen Hsu, Hsin-Yi Chen, Jen-Hui Chuang

Geometry-based camera calibration using principal line is more precise and robust than calibration using optimization approaches; therefore, several researches try to re-derive the principal line from different views of 2D projective geometry to increase alternatives of the calibration process. In this report, algebraical equivalence of two expressions of principal line, one derived w.r.t homography and the other using for two sets of orthogonal vanishing points, is proved. Moreover, the extension of the second expression to incorporate infinite vanishing point is carried out with simple mathematics.

📄 PDF Abstract BibTeX arXiv:2301.03039

Code (0)

등록된 구현이 없습니다.

Tasks

Camera CalibrationVocal Bursts Valence Prediction

Similar Papers 제목 키워드 기반

A PCA based Keypoint Tracking Approach to Automated Facial Expressions Encoding

2024-06-13 · Shivansh Chandra Tripathi, Rahul Garg

The Facial Action Coding System (FACS) for studying facial expressions is manual and requires significant effort and expertise. This paper explores the use of automated techniques to generate Action Units (AUs) for study…

Learning Axioms to Compute Verifiable Symbolic Expression Equivalence Proofs Using Graph-to-Sequence Networks

2021-01-01 · Steven James Kommrusch, Louis-Noel Pouchet, Theo Barolett

We target the problem of proving the semantic equivalence between two complex expressions represented as typed trees, and demonstrate our system on expressions from a rich multi-type symbolic language for linear algebra.…

Graph-to-Sequence

SoftRegex: Generating Regex from Natural Language Descriptions using Softened Regex Equivalence

2019-11-01 · IJCNLP 2019 11 · Jun-U Park, Sang-Ki Ko, Marco Cognetta, Yo-Sub Han

We continue the study of generating se-mantically correct regular expressions from natural language descriptions (NL). The current state-of-the-art model SemRegex produces regular expressions from NLs by rewarding the re…

Proving Equivalence Between Complex Expressions Using Graph-to-Sequence Neural Models

2021-06-01 · Steve Kommrusch, Théo Barollet, Louis-Noël Pouchet

We target the problem of provably computing the equivalence between two complex expression trees. To this end, we formalize the problem of equivalence between two such programs as finding a set of semantics-preserving re…

Graph-to-Sequencevalid

Neural-Network Guided Expression Transformation

2019-02-06 · Romain Edelmann, Viktor Kunčak

Optimizing compilers, as well as other translator systems, often work by rewriting expressions according to equivalence preserving rules. Given an input expression and its optimized form, finding the sequence of rules th…