Localization of acoustic source on solids: A linear predictive coding based algorithm for location template matching

Yap, Xuexin; Khong, Andy W. H.; Gan, Woon‐Seng

doi:10.1109/icassp.2010.5494897

Cited by 11 publications

(12 citation statements)

References 5 publications

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“…More recently, this area of research has found application in the conversion of rigid flat surfaces (such as tabletops and glass panels) into touch interfaces [2] [3] [4] [5]. For such human-computer interface applications, source localization algorithms have been developed to localize the point of impact due to touch using signals acquired by surface-mounted vibration sensors.…”

Section: Introductionmentioning

confidence: 99%

Source localization on solids utilizing time-frequency analysis of parameterized warped signals

Kattukandy

Reju

Khong

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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We propose a new approach for source localization on solids with applications to human-computer interface. We analyze the wave propagation of flexural modes of vibration, generated by an impact on a solid surface, to characterize the dispersive linear time-varying system having non-linear phase response. We show that a difference in dispersion between two signals propagating through solids can be mapped directly to the relative propagation distance if the signals are appropriately time-warped. We then exploit this important property for source localization by computing the similarity of the warped signals in the time-frequency domain. As the proposed source localization algorithm jointly estimates warping-based polynomial parameters and source location, the method does not require pre-calibration.Index Terms-Human-computer interaction, frequency dispersion, source localization on solids, unitary warping.

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Section: Introductionmentioning

confidence: 99%

Source localization on solids utilizing time-frequency analysis of parameterized warped signals

Kattukandy

Reju

Khong

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…Using I = 3 and Q = 25, the accuracy of using CC-LTM and AP-LTM are 68.00% and 96.48% respectively [49], [50]. From this, it is noted that even with reduced complexity, the AP-LTM is able to localize approximately 25% more accurately than the cross-correlation approach.…”

Section: Experimental Results Of Cc-ltm and Ap-ltmmentioning

confidence: 88%

“…The algorithm assumes that the speed of wave propagating is known and that the wave propagates at a constant speed throughout the material. The key advantage of the TDOA-based algorithms over that of the LTM-based algorithms, described in Section 4.3, source localization on solids is that it requires only minimal calibration before it can be operated by a user [46], [49], [50], [51]. We next reviewed a TDOA algorithm which is robust to dispersion and we look at the hardware used to implement the dispersion-robust TDOA algorithm.Since a TDOA-based source localization algorithm requires more than three sensors, we note that a large number of wires are involved in the setup of this prototype.…”

Section: Resultsmentioning

confidence: 99%

“…3.5, a Murata PKS1-4A1 accelerometer is mounted at (5, 25) cm on a piece of acrylic of dimension 60 cm × 30 cm × 0.7 cm. We We propose to evaluate the performance of the algorithms by means of a weighted function defined as [46], [49], [50] 12) where J(Q) is the score of the Q th test tap for Q = 1, . .…”

Section: Experimental Setup and Performance Measurementioning

confidence: 99%

“…calization in solids, where the authors of [14] introduced the use of cross-correlation as a means to compare the similarity between the test signal and the pre-recorded signals. We then propose to model the dominant peaks of the taps using an AP filter model, and show that the AP-LTM is able to localize more accurately than CC-LTM, whilst ensuring a significantly lower computational complexity [49], [50].…”

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confidence: 99%

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Source localization on solids for touch interfaces

Yap¹

Self Cite

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Research into human computer interface (HCI) has been very active in recent years due to the advances in software applications. Such devices are aimed at providing a more natural interface for which humans to interact with machines. In this research, we propose a new approach to the development of a touch interface through the use of a surface-mounted sensor which allows one to convert hard surfaces into touch pads. We first develop, using mechanical vibration theories, a mathematical model that simulates the output signals derived from sensors mounted on a physical surface. Utilizing this model, we determine the hardware required for this research. We then develop a source localization algorithm based on an all-pole filter model for location template matching that extracts the dominant frequencies of the tap. The performance of the proposed algorithm is compared with existing approaches and verified both in a synthetic as well as a real environment for the localization of a finger tap on a touch interface. In addition, we explore the time-difference-of-arrival based methods for source localization and implement a real-time wireless source localization prototype. 4 ACKNOWLEDGEMENT I would like to acknowledge and extend my heartfelt gratitude to the persons who have made assisted and guided me thus far in this research, in particular, the members of the Speech, Touch and Acoustic Tangible Interfaces for Nextgeneration Applications (STATINA), for their continual support, guidance and encouragement, (in alphabetical order) Amir bin Sulaiman,

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Face recognition using a new compressive sensing-based feature extraction method

Banitalebi-Dehkordi

Abouei

et al. 2017

Multimed Tools Appl

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Localization of acoustic source on solids: A linear predictive coding based algorithm for location template matching

Cited by 11 publications

References 5 publications

Source localization on solids utilizing time-frequency analysis of parameterized warped signals

Source localization on solids utilizing time-frequency analysis of parameterized warped signals

Source localization on solids for touch interfaces

Face recognition using a new compressive sensing-based feature extraction method

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