Multi-object tracking using binary masks

Huttunen, Sami; Heikkilä, Janne

doi:10.1109/icip.2008.4712336

Cited by 3 publications

(8 citation statements)

References 7 publications

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“…One of the benefits of this approach is also that neither iterations nor long measurement history are needed. The basic idea of the Kalman-EM algorithm was originally presented by Hannuksela et al (2007) and later it was used for multi-object tracking for the first time (Huttunen and Heikkilä, 2008). Here we extend the previous work (Huttunen and Heikkilä, 2008), and propose a new method for tracking multiple objects from image sequences using detector responses as measurements.…”

Section: Introductionmentioning

confidence: 77%

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Multi-Object Tracking Based on Soft Assignment of Detection Responses

Huttunen

Heikkilä

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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We introduce a new detection-based method that is able to track multiple objects from a single camera. The method is built upon an approach that combines Kalman filtering and the Expectation Maximization (EM) algorithm. The benefit of this approach is that soft assignment of the detections to corresponding objects can be performed automatically using their a posteriori probabilities. This is a general approach for detectionbased multi-object tracking, and there are various ways to detect the objects. In this paper, we demonstrate the applicability of the approach for tracking multiple pedestrians and faces using a basic cascade detector.

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Section: Introductionmentioning

confidence: 77%

“…In addition, the proposed method is able to adjust the scale of the objects tracked. The method presented by Huttunen and Heikkilä (2008) does not provide any of these capabilities.…”

Section: Introductionmentioning

confidence: 99%

Multi-Object Tracking Based on Soft Assignment of Detection Responses

Huttunen

Heikkilä

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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“…It would be possible to utilize the MSER regions directly as a source of location measurements in a Kalman filter based tracker but because of frequently occurring detection errors that do not usually follow Gaussian distribution this would easily lead to tracking failures. In order to alleviate this problem we have applied the multiobject tracking approach proposed by Huttunen & Heikkilä (2008) that is based on probabilistic data association where soft assignments of the measurements are used instead of hard assignments. The basic idea in this method is to detect the objects several times from the same frame with varying detector settings and compute soft assignments for each output.…”

Section: Kalman Filtermentioning

confidence: 99%

“…A probabilistic data association scheme is embedded to the Kalman filter framework to enable multiobject tracking. More details of the data association algorithm can be found from Huttunen & Heikkilä (2008).…”

Section: Kalman Filtermentioning

confidence: 99%

“…In addition to automatic cell segmentation of single still images, we combined MSER with a Kalman filter based tracker modified for multiple objects (Huttunen & Heikkilä, 2008). This tracking approach uses segmentation masks as a source of measurements and utilizes soft assignment to associate the observations to the objects being tracked.…”

Section: Introductionmentioning

confidence: 99%

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Automatic detection and analysis of cell motility in phase‐contrast time‐lapse images using a combination of maximally stable extremal regions and Kalman filter approaches

Kaakinen

Huttunen

Paavolainen

et al. 2013

Journal of Microscopy

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SummaryPhase-contrast illumination is simple and most commonly used microscopic method to observe nonstained living cells. Automatic cell segmentation and motion analysis provide tools to analyze single cell motility in large cell populations. However, the challenge is to find a sophisticated method that is sufficiently accurate to generate reliable results, robust to function under the wide range of illumination conditions encountered in phase-contrast microscopy, and also computationally light for efficient analysis of large number of cells and image frames. To develop better automatic tools for analysis of low magnification phase-contrast images in time-lapse cell migration movies, we investigated the performance of cell segmentation method that is based on the intrinsic properties of maximally stable extremal regions (MSER). MSER was found to be reliable and effective in a wide range of experimental conditions. When compared to the commonly used segmentation approaches, MSER required negligible preoptimization steps thus dramatically reducing the computation time. To analyze cell migration characteristics in time-lapse movies, the MSER-based automatic cell detection was accompanied by a Kalman filter multiobject tracker that efficiently tracked individual cells even in confluent cell populations. This allowed quantitative cell motion analysis resulting in accurate measurements of the migration magnitude and direction of individual cells, as well as characteristics of collective migration fax: +358 8 537 6115; e-mail: lauri.eklund@oulu.fi of cell groups. Our results demonstrate that MSER accompanied by temporal data association is a powerful tool for accurate and reliable analysis of the dynamic behaviour of cells in phase-contrast image sequences. These techniques tolerate varying and nonoptimal imaging conditions and due to their relatively light computational requirements they should help to resolve problems in computationally demanding and often time-consuming large-scale dynamical analysis of cultured cells.

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The interplay of matrix metalloproteinase-8, transforming growth factor-β1 and vascular endothelial growth factor-C cooperatively contributes to the aggressiveness of oral tongue squamous cell carcinoma

et al. 2017

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Background:Matrix metalloproteinase-8 (MMP-8) has oncosuppressive properties in various cancers. We attempted to assess MMP-8 function in oral tongue squamous cell carcinoma (OTSCC).Methods:MMP-8 overexpressing OTSCC cells were used to study the effect of MMP-8 on proliferation, apoptosis, migration, invasion and gene and protein expression. Moreover, MMP-8 functions were assessed in the orthotopic mouse tongue cancer model and by immunohistochemistry in patient samples.Results:MMP-8 reduced the invasion and migration of OTSCC cells and decreased the expression of MMP-1, cathepsin-K and vascular endothelial growth factor-C (VEGF-C). VEGF-C was induced by transforming growth factor-β1 (TGF-β1) in control cells, but not in MMP-8 overexpressing cells. In human OTSCC samples, low MMP-8 in combination with high VEGF-C was an independent predictor of poor cancer-specific survival. TGF-β1 treatment also restored the migration of MMP-8 overexpressing cells to the level of control cells. In mouse tongue cancer, MMP-8 did not inhibit metastasis, possibly because it was eliminated in the peripheral carcinoma cells.Conclusions:The suppressive effects of MMP-8 in OTSCC may be mediated through interference of TGF-β1 and VEGF-C function and altered proteinase expression. Together, low MMP-8 and high VEGF-C expression have strong independent prognostic value in OTSCC.

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Multi-object tracking using binary masks

Cited by 3 publications

References 7 publications

Multi-Object Tracking Based on Soft Assignment of Detection Responses

Multi-Object Tracking Based on Soft Assignment of Detection Responses

Automatic detection and analysis of cell motility in phase‐contrast time‐lapse images using a combination of maximally stable extremal regions and Kalman filter approaches

The interplay of matrix metalloproteinase-8, transforming growth factor-β1 and vascular endothelial growth factor-C cooperatively contributes to the aggressiveness of oral tongue squamous cell carcinoma

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