11709445
Learning user interest for image browsing on small-form-factor devices
Mobile devices which can capture and view pictures are becoming increasingly common in our life. The limitation of these small-form-factor devices makes the user experience of image browsing quite different from that on desktop PCs. In this paper, we first present a user study on how users interact with a mobile image browser with basic functions. We found that on small displays, users tend to use more zooming and scrolling actions in order to view interesting regions in detail. From this fact, we designed a new method to detect user interest maps and extract user attention objects from the image browsing log. This approach is more efficient than image-analysis based methods and can better represent users' actual interest. A smart image viewer was then developed based on user interest analysis. A second experiment was carried out to study how users behave with such a viewer. Experimental results demonstrate that the new smart features can improve the browsing efficiency and are a good compliment to traditional image browsers.
8828427
Detecting geographic locations from web resources
The rapid pervasion of the web into users' daily lives has put much importance on capturing location-specific information on the web, due to the fact that most human activities occur locally around where a user is located. This is especially true in the increasingly popular mobile and local search environments. Thus, how to correctly and effectively detect geographic locations from web resources has become a key challenge to location-based web applications. In our previous work, we proposed to explicitly distinguish three types of locations for web resources, namely provider location, content location and serving location. Provider location is the physical location of the provider who owns the web resource; content location is the geographic location described in the web content; while serving location is the geographic scope that a web resource can reach. In this paper, we present a system that comprehensively employs a set of algorithms and different geographic sources by extracting geographic information from the web content, and mining hyperlink structures as well as user logs. As the result, only relevant geographic sources, rather than all of possible ones are used in computation of each category of web location. Finally, experimental results on large samples of web data show that our solution outperforms previous approaches.
18003538
Automatic Synchronized Browsing of Images Across Multiple Devices
Mobile devices are undergoing considerable progress during recent years. Using these portable devices, people can easily capture and share photos even when they are on the move. Doubtlessly, browsing a large number of images on such small-form-factor devices is still hard and time-consuming, especially when they are distributed across various devices. In this paper, we propose a novel synchronized approach to facilitate image browsing across multiple devices. In this approach, similar images across multiple devices can be simultaneously presented for users to make comparatively viewing or searching. Experimental results show that the synchronized approach is beneficial to improve users' browsing experience.
18031163
Browsing large pictures under limited display sizes
Pictures have become increasingly common and popular in mobile communications. However, due to the limitation of mobile devices, there is a need to develop new technologies to facilitate the browsing of large pictures on the small screen. In this paper, we propose a set of novel approaches which are able to aid or automate common image browsing tasks on mobile devices. All of these approaches are based on an image attention model which is employed to illustrate the information structure within an image. An efficient algorithm to generate the optimal browsing path based on the information foraging theory is presented. Experimental evaluations of the proposed mechanism indicate that our approach is an effective way for viewing large images on small displays
7137580
Adapting Web pages for small-screen devices
We propose a page-adaptation technique that splits existing Web pages into smaller, logically related units. To do this, we must first solve two technical problems: how to detect an existing Web page's semantic structure, and how to split a Web page into smaller blocks based on that structure. To date, we've implemented our technique in Web browsers for mobile devices, in a proxy server for adapting Web pages on the fly, and as an authoring tool plug-in for converting existing Web pages. The Web page can then be adapted to form a two-level hierarchy with a thumbnail representation at the top level for providing a global view and an index to a set of subpages at the bottom level for detailed information.
37379077
Improving Web Browsing on Small Devices Based on Table Classification
Browsing large web pages on small screens is still very inconvenient due to their limited display sizes. A straightforward solution is eliminating the annoying horizontal scrolling requirement, i.e. present all the contents into a single narrow column, usually named one-column view. It is implemented by deleting the layout that will cause horizontal scrolling. However, after deleting the layout structure, some structural information becomes unreadable, like data tables. In this paper, we propose an approach to improve web browsing on small devices by classifying HTML tables into data tables and layout tables. For data tables, we try to preserve the original structural information in the final presentation. Therefore, the browsing experience can be improved for the one-column view. Experimental results show that our approach can achieve a satisfactory performance.
7804224
Level-set based geometric colour snake with region support
A novel method is introduced to force a geometric-based snake be more tolerant towards weak edges and noise in images. The method integrates gradient flow forces with region constraints obtained from diffused region segmentation forces. The diffusion is obtained from the region map vector flow field. This extra region force gives the snake a global view of the boundary information within the image. We present results on both graylevel and colour images.
11201868
Equivalence of Backpropagation and Contrastive Hebbian Learning in a Layered Network
Backpropagation and contrastive Hebbian learning are two methods of training networks with hidden neurons. Backpropagation computes an error signal for the output neurons and spreads it over the hidden neurons. Contrastive Hebbian learning involves clamping the output neurons at desired values and letting the effect spread through feedback connections over the entire network. To investigate the relationship between these two forms of learning, we consider a special case in which they are identical: a multilayer perceptron with linear output units, to which weak feedback connections have been added. In this case, the change in network state caused by clamping the output neurons turns out to be the same as the error signal spread by backpropagation, except for a scalar prefactor. This suggests that the functionality of backpropagation can be realized alternatively by a Hebbian-type learning algorithm, which is suitable for implementation in biological networks.
10241359
Localising surface defects in random colour textures using multiscale texem analysis in image eigenchannels
A novel method is presented to detect defects in random colour textures which requires only a very few normal samples for unsupervised training. We decorrelate the colour image by generating three eigenchannels in each of which the surface texture image is divided into overlapping patches of various sizes. Then, a mixture model and EM is applied to reduce groupings of patches to a small number of textural exemplars, or texems. Localised defect detection is achieved by comparing the learned texems to patches in the unseen image eigenchannels.
22043660
Colour tonality inspection using eigenspace features
In industrial quality inspection of colour texture surfaces, such as ceramic tiles or fabrics, it is important to maintain a consistent colour shade or tonality during production. We present a multidimensional histogram method using a novelty detection scheme to inspect the surfaces. The image noise, introduced by the imaging system, is found mainly to affect the chromatic channels. For colour tonality inspection, the difference between images is very subtle and comparison in the noise dominated chromatic channels is error prone. We perform vector-ordered colour smoothing and extract a localised feature vector at each pixel. The resulting histogram represents an encapsulation of local and global information. Principal component analysis (PCA) is performed on this multidimensional feature space of an automatically selected reference image to obtain reliable colour shade features, which results in a reference eigenspace. Then unseen product images are projected onto this eigenspace and compared for tonality defect detection using histogram comparison. The proposed method is compared and evaluated on a data set with groundtruth.
14041261
Discount auctions for procuring heterogeneous items
e-Procurement is an Internet based business process for sourcing direct or indirect materials. In this paper we propose an auction mechanism called as discount auctions for procuring multiple items. The bid from a supplier consists of individual costs for each of the items and a discount function, which specifies the discount over the number of items. We show that such a bid is more meaningful and cost effective in terms of bid preparation and communication in common procurement scenarios. The bid evaluation problem is modeled as a mixed integer linear program and various structures in the problem that can be exploited for developing algorithms are explored. A heuristic based on linear programming relaxation is proposed to determine a feasible solution to the problem and its closeness to optimality is studied with computational experiments.