KINEMATIC AND ACOUSTIC OPTIMIZATION OF CAMERA AND AUDIO RECORDING SYSTEMS FOR ENHANCED MEDIA PRODUCTION — REVIEW

Shantanu Kale; Narendra R. Deore

doi:10.29121/shodhkosh.v5.i1.2024.6320

Authors

Shantanu Kale Individual Researcher
Narendra R. Deore Professor, Department of Mechanical Engineering, Pimpri Chinchwad College of Engineering, Pune, India.

DOI:

https://doi.org/10.29121/shodhkosh.v5.i1.2024.6320

Keywords:

Camera Kinematics, Beamforming, Room Acoustics, Trajectory Planning, Audiovisual Synchronization, Pareto Optimization, Microphone Arrays, Stabilization

Abstract [English]

The convergence of camera kinematics and acoustic optimization has emerged as a crucial frontier in media production. Traditionally, cinematography and audio engineering have been treated as parallel but independent workflows, often resulting in trade-offs between visual framing and sound fidelity. This review synthesizes advances in kinematic modeling, trajectory planning, stabilization systems, and learning-based cinematography alongside parallel developments in microphone directivity, beamforming, room acoustics, and adaptive noise control. By examining these domains jointly, we highlight how multi-objective formulations and Pareto-front trade-offs can guide camera placement, path planning, and acoustic treatment to maximize perceptual quality of experience (QoE) for audiences. Special emphasis is placed on audiovisual alignment, motor noise mitigation, and the role of on-set compute for real-time optimization in broadcast, film, virtual reality, and live event contexts. The paper also reviews key datasets, simulators, and open-source tools that support benchmarking, reproducibility, and system integration. Contributions of this work include mapping the foundations of joint kinematic–acoustic design, identifying gaps in metrics and evaluation, and providing guidelines for future research and deployment. The review serves as a resource for academics, engineers, and creative professionals seeking to advance immersive media production.

References

T. Villgrattner, “Design and control of a compact high-dynamic camera-orientation systems,” Ph.D. dissertation, Technische Universität München, accepted 21 Oct. 2010. [Online]. Available via IEEE Xplore (via ResearchGate).

T. Villgrattner, “Design and control of a compact high-dynamic camera-orientation systems,” IEEE Xplore, Dec. 2010. [Online]. Available via IEEE Xplore.

Calibrating and optimizing poses of visual sensors in distributed platforms, Multimedia Systems, vol. 12, pp. 195–210, Oct. 2006. [Online]. Available via SpringerLink. DOI: https://doi.org/10.1007/s00530-006-0057-6

P. Rahimian and J. K. Kearney, “Optimal camera placement for motion capture systems in the presence of dynamic occlusion,” in Proc. 21st ACM Symposium, Nov. 2015, DOI: 10.1145/2821592.2821596. [Online]. Available via ResearchGate. DOI: https://doi.org/10.1145/2821592.2821596

Y. Feng and L. Max, “Accuracy and precision of a custom camera-based system for 2D and 3D motion tracking during speech and nonspeech motor tasks,” J. Speech Lang. Hear. Res., vol. 57, no. 2, pp. 426–438, Apr. 2014. [Online]. Available via PMC. DOI: https://doi.org/10.1044/2014_JSLHR-S-13-0007

L. Zhou et al., "Graph Neural Networks for Decentralized Multi-Robot Target Tracking," 2022 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Sevilla, Spain, 2022, pp. 195-202, doi: 10.1109/SSRR56537.2022.10018712. DOI: https://doi.org/10.1109/SSRR56537.2022.10018712

R. Bonatti et al., “Autonomous aerial cinematography in unstructured environments with learned artistic decision-making,” arXiv, Oct. 2019. [Online]. Available via arXiv.

Jiang, H., Wang, B., Wang, X., Christie, M., Chen, B.: Example-driven virtual cinematography by learning camera behaviors. ACM Trans. Graphics (TOG) 39(4), 45:1–45:14 (2020) DOI: https://doi.org/10.1145/3386569.3392427

G. Zhu et al., “A high-speed imaging method based on compressive sensing for sound extraction using a low-speed camera,” Sensors, vol. 18, no. 5, Art. 1524, 2018. [Online]. Available via MDPI. DOI: https://doi.org/10.3390/s18051524

Absolute geometry calibration of distributed microphone arrays in an audio-visual sensor network, arXiv, Apr. 2015. [Online]. Available via arXiv.

“Acoustic camera,” Wikipedia, latest edit. [Online]. Available via Wikipedia.

“3D sound localization,” Wikipedia, latest edit. [Online]. Available via Wikipedia.

M. Brandstein, H. Silverman, et al., “A practical methodology for speech source localization with microphone arrays,” Computer, Speech and Language, vol. 11, no. 2, 1997. [Online]. Available via SpringerLink. DOI: https://doi.org/10.1006/csla.1996.0024

H. Wang and P. Chu, “Voice source localization for automatic camera pointing system in videoconferencing,” in Proc. ICASSP97, Munich, Germany, Apr. 20–24, 1997. [Online]. Available via SpringerLink.

J. Dmochowski and J. Benesty, “Steered beamforming approaches for acoustic source localization,” in Speech Processing in Modern Communication, Springer, 2010. [Online]. Used as reference context. DOI: https://doi.org/10.1007/978-3-642-11130-3_12

B. Rafaely, Fundamentals of Spherical Array Processing, Springer, 2019. [Online]. Used as reference context. DOI: https://doi.org/10.1007/978-3-319-99561-8

B. Van Veen and K. Buckley, “Beamforming: A versatile approach to spatial filtering,” IEEE ASSP Magazine, vol. 5, no. 2, pp. 4–24, 1988. [Online]. Used as reference context. DOI: https://doi.org/10.1109/53.665

N. Saeed et al., “Optical camera communications: Survey, use cases, challenges, and future trends,” arXiv, Dec. 2018. [Online]. Available via arXiv. DOI: https://doi.org/10.1016/j.phycom.2019.100900

A. Gerami et al., “A hybrid kinematic-acoustic system for automated activity detection of construction equipment,” Sensors, vol. 19, no. 19, 2019. [Online]. Available via MDPI. DOI: https://doi.org/10.3390/s19194286

“A feasibility study for a hand-held acoustic imaging camera,” Applied Sciences, vol. 13, no. 19, Art. 11110, 2023. [Online]. Available via MDPI. DOI: https://doi.org/10.3390/app131911110