Structured partial least squares for simultaneous object tracking and segmentation

Zhong, Bineng; Yuan, Xin; Ji, Rongrong; Yan, Yan; Cui, Zhen; Hong, Xiaopeng; Chen, Yan; Tian, Wei; Duan-sheng, Chen; Yu, Jiaxin

doi:10.1016/j.neucom.2013.11.004

Cited by 16 publications

(6 citation statements)

References 24 publications

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“…Tracking. Several tracking-by-segmentation methods [9,12,11,28] have been developed in the literature. In [9], a level-set formulation is presented to accurately extract object boundaries for tracking.…”

Section: Related Work and Problem Contextmentioning

confidence: 99%

JOTS: Joint Online Tracking and Segmentation

Wen

Lei

et al. 2015

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

100

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We present a novel Joint Online Tracking and Segmentation (JOTS) algorithm which integrates the multi-part tracking and segmentation into a unified energy optimization framework to handle the video segmentation task. The multi-part segmentation is posed as a pixel-level label assignment task with regularization according to the estimated part models, and tracking is formulated as estimating the part models based on the pixel labels, which in turn is used to refine the model. The multi-part tracking and segmentation are carried out iteratively to minimize the proposed objective function by a RANSAC-style approach. Extensive experiments on the SegTrack and SegTrack v2 databases demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods.

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Section: Related Work and Problem Contextmentioning

confidence: 99%

JOTS: Joint Online Tracking and Segmentation

Wen

Lei

et al. 2015

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

100

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“…PLS is an algorithm that is used to fit the relationships of variables to two or more independent variables. (20)(21)(22) Prediction data of PLS were divided into several regions described by the feature vector. In the same regions, vectors are orthogonal to each other; in the different regions, vectors are associated with the model based on the previous channel.…”

Section: Plsmentioning

confidence: 99%

Partial Least Square-Support Vector Machine for Rapid Detection of Egg Storage Life by Chemometric Processing of Voltammetric Signals

2016

Sensors and Materials

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The rapid detection of the grade and storage life of eggs is important for consumers and producers. In this study, an electrochemical system based on voltammetry was used for the rapid detection of egg yolk and egg white mixtures for classification and prediction of storage days. Measuring the Haugh units (H.U.) index of Lindian eggs is aimed at identifying the grades of these eggs and the corresponding storage days. Discriminant function analysis was used to identify accurately the grades of eggs on the basic of storage life. The Gaussian kernel function and a suitable penalty factor were selected to establish a support vector machine for predicting the storage days of eggs. By avoiding deviation in the result due to the correlation of data, which was acquired by square-wave voltammetry technology, the partial least squares and support vector machine were combined, and the predictive accuracy of egg storage days was improved by up to 97.14%. A tenfold cross-validation has been used to evaluate the classification performance of the model; the average accuracy of prediction of storage life was 88.57%.

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“…However, in reality, objects have different degrees of relatedness based on different views (e.g., conceptual similarity based on WordNet or visual similarity based on visual features). The same issues would happen in the tracking problems, too [23,24]. Thus, a good semantic hierarchy should incorporate these different degrees of relatedness to provide a better understanding of image semantics.…”

Section: Introductionmentioning

confidence: 96%