Real Time Face Tracking with Pyramidal Lucas-Kanade Feature Tracker

Kim, Ki-sang; Jang, Daesik; Choi, Hyung-Il

doi:10.1007/978-3-540-74472-6_89

Cited by 8 publications

(3 citation statements)

References 5 publications

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“…The purpose of image point tracking is to find the matching pixel point N in the image to be matched for the pixel point M in the specified reference image I, or to calculate the optical flow V of the point M, where V = (u, v) T . Assuming that the coordinates of the point M in the original image I are (M x , M y ), and M L = (M L x , M L y ) is the value of the coordinates of the point M in the Lth level pyramid image, M L = M/2 L , which is known from the principle of image pyramid formation [17].…”

Section: Tracking Pixels Through Pyramid Imagesmentioning

confidence: 99%

Two-Dimensional Flow Field Measurement Method for Sediment-Laden Flow Based on Optical Flow Algorithm

Tao

Liu

et al. 2022

Applied Sciences

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This paper proposes a novel particle image velocimetry (PIV) technique to generate an instantaneous two-dimensional velocity field for sediment-laden fluid based on the optical flow algorithm of ultrasound imaging. In this paper, an ultrasonic PIV (UIV) system is constructed by integrating a medical ultrasound instrument and an ultrasonic particle image velocimetry algorithm. The medical ultrasound instrument with a phased sensor array is used to acquire acoustic echo signals of particles in water and generate two-dimensional underwater ultrasound images. Based on the optical flow field, the instantaneous velocity of the particles in water corresponding to the pixels in the ultrasonic particle images is derived from the grayscale change between adjacent images under the L-K local constraint based on the optical flow field, and finally, the two-dimensional flow field is obtained. Through multiple sets of experiments, the proposed algorithm is verified. The experimental results are compared with those of the conventional cross-correlation algorithms. The results show that the L-K optical flow method can not only obtain the underwater velocity field accurately, but also has the advantages of good smoothness and extensive suitability, especially for the flow field measurement in sediment-laden fluid than conventional algorithms.

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Section: Tracking Pixels Through Pyramid Imagesmentioning

confidence: 99%

Two-Dimensional Flow Field Measurement Method for Sediment-Laden Flow Based on Optical Flow Algorithm

Tao

Liu

et al. 2022

Applied Sciences

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“…is the value of the coordinates of the point M in the Lth level pyramid image, M L = M/2 L , which is known from the principle of image pyramid formation Kim et al (2007).…”

Section: Tracking Pixels Through Pyramid Imagesmentioning

confidence: 99%

Two-dimensional flow field measurement of sediment-laden flow based on ultrasound image velocimetry

Wei

Liu²,

Ma³

et al. 2021

Preprint

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This paper proposes a novel particle image velocimetry (PIV) technique to generate an instantaneous two-dimensional velocity field for sediment-laden fluid based on optical flow algorithm of ultrasound imaging. In this paper, an ultrasonic PIV (UPIV) system is constructed by integrating a medical ultrasound instrument and an ultrasonic particle image velocimetry algorithm. The medical ultrasound instrument with a phased sensor array is used to acquire acoustic echo signals and generate two-dimensional underwater ultrasound images. Based on the optical flow field, the instantaneous velocity of the particles in water corresponding to the pixels in the ultrasonic particle images is derived from the grayscale change between adjacent images under the L-K local constraint, and finally the two-dimensional flow field is obtained. Through multiple sets of experiments, the proposed algorithm is verified. The experimental results are compared with those of the conventional cross-correlation algorithms. The results show that the L-K optical flow method can not only obtain the underwater velocity field accurately, but also has the advantages of good smooothness and extensive suitability, specially for the flow field measurement in sediment-laden fluid than conventional algorithms.

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“…Recent work in feature tracking and sequential map-building and localization resorts to limiting the number of features considered or the frequency of updates made in order to achieve real-time performance [1], [2], [3]. Alternatively, we explore performance enhancement without result degradation by using hardware accelerators that speed up existing fullfeatured application code.…”

Section: Introductionmentioning

confidence: 99%

Accelerating vision and navigation applications on a customizable platform

Cong

Grigorian

Reinman

et al. 2011

ASAP 2011 - 22nd IEEE International Conference on Application-Specific Systems, Architectures and Processors

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Abstract-The domain of vision and navigation often includes applications for feature tracking as well as simultaneous localization and mapping (SLAM). As these problems require computationally demanding solutions, it is challenging to achieve high performance without sacrificing the fidelity of results or otherwise consuming excessive amounts of energy. Our goal then is to accelerate the applications in this domain to meet real-time performance constraints while simultaneously reducing energy consumption and avoiding degradation in the quality of results. To achieve this domain-specific acceleration, we model a customizable hardware platform based on the 3D integration of a Field-Programmable Gate Array (FPGA) atop a standard chip multiprocessor (CMP) with Through-Silicon Vias (TSVs) used for communication between the two layers. Furthermore, partial automation of accelerator creation using C-to-RTL tools allows for analysis of a wide range of candidates. In this work, we mathematically characterize viable accelerator candidates, describe ideal application code for acceleration, and outline a dynamic-programming-based methodology for selecting an optimal set of candidates. Our results yield an overall speedup and energy reduction of 9.56X along with a 94X EDP reduction for the domain. Finally, we investigate the effects of various interconnect models on our performance improvements. Overall, our proposed system is shown to be highly efficient in both accelerating performance and saving energy for compute-intensive applications in this domain.

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Real Time Face Tracking with Pyramidal Lucas-Kanade Feature Tracker

Cited by 8 publications

References 5 publications

Two-Dimensional Flow Field Measurement Method for Sediment-Laden Flow Based on Optical Flow Algorithm

Two-Dimensional Flow Field Measurement Method for Sediment-Laden Flow Based on Optical Flow Algorithm

Two-dimensional flow field measurement of sediment-laden flow based on ultrasound image velocimetry

Accelerating vision and navigation applications on a customizable platform

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