Model-Based Approach for Shadow Detection of Static Images

False tracking is the biggest problem identified in tracking. The reasons for this is identified as shadow of the object to be tracked which have their shape mapping to the shape of the object. Dynamic shadow detection is the field in which videos are used. Dynamic shadow detection is found to be more exposed in literature due to the possibility of comparison, frame differentiation, background subtraction. All this not being possible in case of static images as they represent a single frame and are not used to that extent. Taking this as a challenge this paper presents static shadow detection in which the static shadow detection methods are mapped with dynamic images within the domain of image processing.The results so obtained are then authenticated from the user side. Every user may have different views, so as to bring the evaluation at a standard level this qualitative evaluation is quantified so as to be represented in form of tables and graphs for further analysis.

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A model-based approach for estimating human 3D poses in static images

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2006.110 ◽

2006 ◽

Vol 28 (6) ◽

pp. 905-916 ◽

Cited By ~ 69

Author(s):

Mun Wai Lee ◽

I. Cohen

Keyword(s):

Model Based ◽

Static Images

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

2001 ◽

Vol 7 (S2) ◽

pp. 578-579

Author(s):

David W. Knowles ◽

Sophie A. Lelièvre ◽

Carlos Ortiz de Solόrzano ◽

Stephen J. Lockett ◽

Mina J. Bissell ◽

...

Keyword(s):

Image Analysis ◽

Mammary Epithelial Cells ◽

Nuclear Organization ◽

Critical Role ◽

Quantitative Model ◽

Mammary Epithelial ◽

Cell Phenotype ◽

Proliferating Cells ◽

Mitotic Apparatus ◽

Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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