From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques

Semra Çelebi; İbrahim Türkoğlu

doi:10.35377/saucis...1718848

From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques

Abstract

This study explores the current state, core methodologies, and major challenges associated with non-line-of-sight (NLOS) sensing technologies. NLOS sensing enables the detection of objects and individuals outside the direct field of view and has critical applications in disaster response, security, and autonomous systems. Despite its growing potential, the field faces technical limitations, including restricted resolution, complex data processing, and multipath propagation effects. A wide range of approaches is examined, including both active and passive systems, SPAD and CCD/CMOS sensors, confocal and non-confocal imaging techniques, acoustic methods, and artificial intelligence-based models. The study also emphasizes innovative experimental setups and complex scene designs to evaluate system performance under realistic and challenging conditions. Furthermore, diverse evaluation metrics are discussed to support both numerical and perceptual analysis of system outputs. In conclusion, NLOS sensing is a complex field that requires an interdisciplinary approach, but it holds great potential for the scientific community and practitioners due to the opportunities it offers. This study has contributed to the current body of knowledge and provided suggestions that will guide future research.

Keywords

References

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Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Review

Authors

Semra Çelebi ^*
0000-0002-5339-8695
Türkiye

İbrahim Türkoğlu
0000-0003-4938-4167
Türkiye

Early Pub Date

March 30, 2026

Publication Date

March 30, 2026

Submission Date

June 13, 2025

Acceptance Date

November 18, 2025

Published in Issue

Year 2026 Volume: 9 Number: 1

DOI

https://doi.org/10.35377/saucis...1718848

IZ

https://izlik.org/JA34EG23LX

Cite

RIS / Bibtex

APA

Çelebi, S., & Türkoğlu, İ. (2026). From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques. Sakarya University Journal of Computer and Information Sciences, 9(1), 262-291. https://doi.org/10.35377/saucis...1718848

AMA

1.Çelebi S, Türkoğlu İ. From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques. SAUCIS. 2026;9(1):262-291. doi:10.35377/saucis.1718848

Chicago

Çelebi, Semra, and İbrahim Türkoğlu. 2026. “From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques”. Sakarya University Journal of Computer and Information Sciences 9 (1): 262-91. https://doi.org/10.35377/saucis. 1718848.

EndNote

Çelebi S, Türkoğlu İ (March 1, 2026) From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques. Sakarya University Journal of Computer and Information Sciences 9 1 262–291.

IEEE

[1]S. Çelebi and İ. Türkoğlu, “From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques”, SAUCIS, vol. 9, no. 1, pp. 262–291, Mar. 2026, doi: 10.35377/saucis...1718848.

ISNAD

Çelebi, Semra - Türkoğlu, İbrahim. “From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques”. Sakarya University Journal of Computer and Information Sciences 9/1 (March 1, 2026): 262-291. https://doi.org/10.35377/saucis. 1718848.

JAMA

1.Çelebi S, Türkoğlu İ. From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques. SAUCIS. 2026;9:262–291.

MLA

Çelebi, Semra, and İbrahim Türkoğlu. “From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques”. Sakarya University Journal of Computer and Information Sciences, vol. 9, no. 1, Mar. 2026, pp. 262-91, doi:10.35377/saucis. 1718848.

Vancouver

1.Semra Çelebi, İbrahim Türkoğlu. From Traditional Methods to Artificial Intelligence: A Review of Non-Line-of-Sight Analysis Techniques. SAUCIS. 2026 Mar. 1;9(1):262-91. doi:10.35377/saucis. 1718848