Visual structure and the integration of form and color information.

Author(s):  
Beena Khurana
2006 ◽  
Author(s):  
Andrea N. Eslick ◽  
Bogdan Kostic ◽  
Anne M. Cleary

Semiotica ◽  
2018 ◽  
Vol 2018 (220) ◽  
pp. 123-153
Author(s):  
Andrea Rocci ◽  
Sabrina Mazzali-Lurati ◽  
Chiara Pollaroli

AbstractThe aim of this article is to contribute to the theoretical development of multimodal metonymy and the argumentative and rhetorical role that the trope can fulfil in multimodal advertising campaigns. A model for the analysis of multimodal tropes in page-based advertising messages is developed by drawing insights from different disciplines. This model involves the identification of the elementary and layout components of the message, the description of its multimodal structure (in terms of the visual structure and the contribution of the verbal component), the reconstruction of its meaning operation, and the reconstruction of its enthymematic structure. In particular, the meaning operation is reconstructed by the employment of Conceptual Integration Theory, which we have slightly revised in order to better account for metonymical mappings. The enthymematic structure is reconstructed following the Argumentum Model of Topics, a model of argument schemes that enables one to make explicit the contextual and the logical dimensions of arguments. Based on the tenets of the two frameworks, we claim that multimodal metonymy condenses and gives access to a complex chain of connections, which mirrors the argumentation the audience is invited to infer. This argumentation is based on causal schemes of reasoning. This claim results in the in-depth analysis of both a billboard belonging to an anti-AIDS campaign and a social campaign by Greenpeace against the use of environmental-damaging paper for toy packages by Mattel.


2001 ◽  
Author(s):  
Panagiotis Androutsos ◽  
Diana Ferrari ◽  
Allen Ly ◽  
Andrew Persaud ◽  
Dimitrios Androutsos ◽  
...  

2011 ◽  
Vol 55-57 ◽  
pp. 77-81
Author(s):  
Hui Ming Huang ◽  
He Sheng Liu ◽  
Guo Ping Liu

In this paper, we proposed an efficient method to address the problem of color face image segmentation that is based on color information and saliency map. This method consists of three stages. At first, skin colored regions is detected using a Bayesian model of the human skin color. Then, we get a chroma chart that shows likelihoods of skin colors. This chroma chart is further segmented into skin region that satisfy the homogeneity property of the human skin. The third stage, visual attention model are employed to localize the face region according to the saliency map while the bottom-up approach utilizes both the intensity and color features maps from the test image. Experimental evaluation on test shows that the proposed method is capable of segmenting the face area quite effectively,at the same time, our methods shows good performance for subjects in both simple and complex backgrounds, as well as varying illumination conditions and skin color variances.


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