Semantic-Preserving Word Clouds by Seam Carving

نویسندگان

  • Yingcai Wu
  • Thomas Provan
  • Furu Wei
  • Shixia Liu
  • Kwan-Liu Ma
چکیده

Abstract Word clouds are proliferating on the Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a collection of documents quickly, their ability to visually compare documents is limited. This paper introduces a new method to create semantic-preserving word clouds by leveraging tailored seam carving, a well-established content-aware image resizing operator. The method can optimize a word cloud layout by removing a left-to-right or top-to-bottom seam iteratively and gracefully from the layout. Each seam is a connected path of low energy regions determined by a Gaussian-based energy function. With seam carving, we can pack the word cloud compactly and effectively, while preserving its overall semantic structure. Furthermore, we design a set of interactive visualization techniques for the created word clouds to facilitate visual text analysis and comparison. Case studies are conducted to demonstrate the effectiveness and usefulness of our techniques.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Content Aware Media Retargeting for still images using Seam Carving

ABSTRACT When changing height and width of image traditional techniques for image resizing are oblivious to the content of image. A simple operator seam carving is used for image and video retargeting. This seam carving operator is used for content aware image resizing to reduce or expand image size. According to seam carving method every object in the image must be scaled down proportionally. ...

متن کامل

Seam Carving for semantic video coding

Compression standards such as H.264/AVC encode video sequences to maximize fidelity at a given bitrate. However, semantic-oriented and content-aware compression remains a challenge. In this paper, we propose a semantic video compression method using seam carving. Seam carving changes the dimension of an image/video with a non-uniform resampling of each row and column while keeping the rectangul...

متن کامل

Improved seam carving for semantic video coding

Traditional video codecs like H.264/AVC encode video sequences to minimize the Mean Squared Error (MSE) at a given bitrate. Seam carving is a content-aware resizing method. In this paper, we propose a semantic video compression scheme based on seam carving. Its principle is to suppress non salient parts of the video by seam carving. The reduced sequence is then encoded with H.264/AVC and the se...

متن کامل

Improved Content Aware Image Retargeting Using Strip Partitioning

Based on rapid upsurge in the demand and usage of electronic media devices such as tablets, smart phones, laptops, personal computers, etc. and its different display specifications including the size and shapes, image retargeting became one of the key components of communication technology and internet. The existing techniques in image resizing cannot save the most valuable information of image...

متن کامل

Seam carving modeling for semantic video coding in security applications

In some security applications, it is important to transmit just enough information to take the right decisions. Traditional video codecs try to maximize the global quality, irrespective of the video content pertinence for certain tasks. To better maintain the semantics of the scene, some approaches allocate more bitrate to the salient information. In this paper, a semantic video compression sch...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Comput. Graph. Forum

دوره 30  شماره 

صفحات  -

تاریخ انتشار 2011