Thumbnail Generation Based on Global Saliency

Computer Vision, 2009 …, 2009

Image cropping is a technique that is used to select the most relevant areas of an image, discarding the useless ones. Handmade selection, especially in case of large photo collections, is a time consuming task. Automatic image cropping techniques may help users, suggesting to them which part of the image is the most relevant, according to specific criteria. We suppose that the most visually salient areas of a photo are also the most relevant ones to the users. In this paper we present an extended version of our previously proposed method, to extract the saliency map of an image, which is based on the analysis of the distribution of the interest points of the image. Three different interest point extraction algorithms are evaluated within an automatic image cropping system, to study the effectiveness of the related saliency maps for this task. We furthermore compared our results with two state of the art saliency detection techniques. Tests have been conducted onto an online available dataset, made of 5000 images which have been manually labeled by 9 users.

2012

Journal of Development Research

Image resizing is a process of processing images or images with the aim of changing the size of the image. The most commonly used methods are cropping or scaling. Scaling is changing the size of the image based on the scale. Contents in the image are not considered in scaling. Seam carving often uses energy functionality that is useful as a determinant of the pixel level contained in an image. Seam is a connecting path of image pixels both vertically and horizontally that is passed by a low energy function. Changing the image size using seam carving is considered better than cropping and scaling. However, the seam carving method still cannot protect the object that is considered the most important. In overcoming this weakness, we can use a combination of seam carving algorithm with salient detection. In this research, we will improve the two methods which function as thumbnail maker. The results of the salient detection of the most important areas of the image will be detected and a...

2012

Abstract In this paper, we deal with the problem of detecting the existence and the location of salient objects for thumbnail images on which most search engines usually perform visual analysis in order to handle web-scale images. Different from previous techniques, such as sliding window-based or segmentation-based schemes for detecting salient objects, we propose to use a learning approach, random forest in our solution.

Cognitive Computation, 2012

2011 IEEE Workshop on Applications of Computer Vision (WACV), 2011

Lecture Notes in Computer Science, 2013

2004