Content-Aware Image Retargeting Based on Semantic Analysis

2014 ◽  
Vol 577 ◽  
pp. 777-781 ◽  
Author(s):  
Hao Cheng ◽  
Wei Li ◽  
Pei Min Zhong
Keyword(s):  
Object Recognition ◽  
Energy Loss ◽  
Energy Function ◽  
Semantic Analysis ◽  
Triangular Mesh ◽  
Image Retargeting ◽  
Complex Scene ◽  
Important Object ◽  
Least Energy ◽  
Content Aware

This paper presents a retargeting approach based on semantic analysis. Our approach has better performance in images that have comlicated backgroud or multi-objects. Our aim is to protect important object in retargeting process. So we brought in object recognition and image importance calculation for retargeting. This approach consists of three parts: object recognition, the importance of image calculation and image retargeting. (i) Firstly we optimized semantic texton forest (STF)[11]and got much better results of object recognition.(ii) Secondly we presented a method called dynamically adjust importance image calculation. (iii) Thirdly we give a retargeting method based on triangular mesh. According to importance image we cover Delaunay triangular mesh on image and solve optimization mesh transforming based on energy function which subjects to least energy loss and boundary restraint. Compared with previous approaches, our method has better result in some complex scene images.

Semantic-Analysis Object Recognition: Automatic Training Set Generation Using Textual Tags

2015 ◽  
pp. 309-322
Author(s):  
Sami Abduljalil Abdulhak ◽  
Walter Riviera ◽  
Nicola Zeni ◽  
Matteo Cristani ◽  
Roberta Ferrario ◽  
...  
Keyword(s):  
Object Recognition ◽  
Semantic Analysis ◽  
Training Set

Object Extraction Using Topological Models from Complex Scene Image

2017 ◽  
pp. 335-357
Author(s):  
Uday Pratap Singh ◽  
Sanjeev Jain
Keyword(s):  
Object Recognition ◽  
Object Segmentation ◽  
Multimedia Data ◽  
Region Merging ◽  
Complex Scene ◽  
Object Contour ◽  
Merging Process ◽  
Feasible Solutions ◽  
Neighbourhood Graph ◽  
Topological Models

Efficient and effective object recognition from a multimedia data are very complex. Automatic object segmentation is usually very hard for natural images; interactive schemes with a few simple markers provide feasible solutions. In this chapter, we propose topological model based region merging. In this work, we will focus on topological models like, Relative Neighbourhood Graph (RNG) and Gabriel graph (GG), etc. From the Initial segmented image, we constructed a neighbourhood graph represented different regions as the node of graph and weight of the edges are the value of dissimilarity measures function for their colour histogram vectors. A method of similarity based region merging mechanism (supervised and unsupervised) is proposed to guide the merging process with the help of markers. The region merging process is adaptive to the image content and it does not need to set the similarity threshold in advance. To the validation of proposed method extensive experiments are performed and the result shows that the proposed method extracts the object contour from the complex background.

Content-aware compression using saliency-driven image retargeting

2013 ◽  
Author(s):  
Fabio Zund ◽  
Yael Pritch ◽  
Alexander Sorkine-Hornung ◽  
Stefan Mangold ◽  
Thomas Gross
Keyword(s):  
Image Retargeting ◽  
Content Aware

Numerical Comparison of Operating Conditions and Nozzle Geometry on Injector Performance

2013 ◽  
Author(s):  
Kun Zhang ◽  
Bo Zhang ◽  
Xu Xiang ◽  
Yong Yang
Keyword(s):  
Energy Loss ◽  
Heat Load ◽  
Area Ratio ◽  
Operating Conditions ◽  
The Other ◽  
Nozzle Geometry ◽  
Operating Parameters ◽  
Numerical Comparison ◽  
Other Hand ◽  
Least Energy

A model was established to discuss the effect of operating parameters and nozzle shapes on the performance of injectors. The comparison pointed out that heat load has worst effect on injector geometries, while little effect on area ratio. On the other hand, the area ratio is very sensitive to suction temperature, which is critical to injector performance. The least energy loss is achieved when nozzle converges gently at the same nozzle entrance and exit diameter.

scholarly journals Content-Aware Image Retargeting Incorporated with Letterboxing

2017 ◽  
Vol E100.D (4) ◽  
pp. 865-873
Author(s):  
Kazu MISHIBA ◽  
Yuji OYAMADA ◽  
Katsuya KONDO
Keyword(s):  
Image Retargeting ◽  
Content Aware

Content-Aware Image Retargeting

2016 ◽  
pp. 115-131
Author(s):  
Rajarshi Pal ◽  
Prasun Chandra Tripathi
Keyword(s):  
Image Retargeting ◽  
Related Research ◽  
Is Evaluation ◽  
Screen Space ◽  
Small Screen ◽  
Content Aware

Displaying a large image in a small screen of a handheld gadget is a challenging task. Simple down-scaling of the image may reduce some objects too small to be perceptible. This gives rise to content-aware retargeting of the image. Important contents are allotted more screen space as compared to relatively less important contents of the image. Various types of content-aware image retargeting approaches have been proposed in a span of just over a decade. Another challenging area is to estimate importance of importance of the contents. Lot of researches has been carried out in this direction too to identify the important contents in the context of image retargeting. Equally important aspect is evaluation of these retargeting methods. This article contains a brief survey of related research in all of these aspects.

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