This abstract propose as-projective-as-possible warps, i.e., warps that aim to be globally projective, yet allow local non-projective deviations to account for violations to the assumed imaging conditions. Based on a novel estimation technique called Moving Direct Linear Transformation (Moving DLT), our method seamlessly bridges image regions that are inconsistent with the projective model. The result […]
A NOVEL HUB-BASED CLUSTERING FOR HIGH-DIMENSIONAL DATA
Clustering becomes difficult due to the increasing sparsity of such data, as well as the increasing difficulty in distinguishing distances between data points. Hubness is the tendency of some data points in high-dimensional data sets to occur much more frequently in k-nearest-neighbor lists of other points than the rest of the points from the set, […]
2D TO STEREOSCOPIC 3D CONVERSION USING ROBUST SEMI-AUTOMATIC DEPTH MAP GENERATION IN UNCONSTRAINED IMAGES AND VIDEO SEQUENCES
Stereoscopic imaging has been around for many decades, it has recently seen a rise in interest due to the availability of consumer 3D displays and 3D films. This surge is seen in the recent proliferation of big budget 3D movies, or with some portions of the film being offered in 3D. 3D films show novel […]
THE ROLE OF HUB-BASED CLUSTERING FOR HIGH-DIMENSIONAL DATA
Clustering in general is an unsupervised process of grouping elements together, so that elements assigned to the same cluster are more similar to each other than to the remaining data points. In this abstract, we take a novel perspective on the problem of clustering high-dimensional data. Instead of attempting to avoid the curse of dimensionality […]
UNCONSTRAINED IMAGES AND VIDEO SEQUENCES CONTAINS ROBUST SEMI-AUTOMATIC DEPTH MAP GENERATION FOR 2D TO STEREOSCOPIC 3D CONVERSION
Our framework relies on the user providing an initial estimate of the depth, where the user marks objects and regions as closer or farther from the camera. We allow the user to mark with monochromatic intensities, as well as a varying color palette from dark to light, serving in the same function as the intensities. […]
A COCKTAIL APPROACH ON PERSONALIZED TRAVEL PACKAGE RECOMMENDATION BASED ON THE TAST MODEL
In this abstract, we first analyze the characteristics of the existing travel packages and develop a tourist-area-season topic (TAST) model. This TAST model can represent travel packages and tourists by different topic distributions, where the topic extraction is conditioned on both the tourists and the intrinsic features (i.e., locations, travel seasons) of the landscapes. Then, […]
THE PROBLEM OF ASSIGNING CLIENTS TO SERVERS FOR MAXIMIZING THE INTERACTIVITY OF DISTRIBUTED INTERACTIVE APPLICATION
Distributed interactive applications (DIAs), such as multiplayer online games and distributed interactive simulations, allow participants at different locations to interact with one another through networks. Thus, the interactivity of DIAs is important for participants to have enjoyable interaction experiences. Normally, interactivity is characterized by the duration from the time when a participant issues an operation […]
COCKTAIL RECOMMENDATION APPROACH FOR TRAVEL PACKAGE
The rapid growth of online travel information imposes an increasing challenge for tourists who have to choose from a large number of available travel packages for satisfying their personalized needs. Moreover, to increase the profit, the travel companies have to understand the preferences from different tourists and serve more attractive packages. Therefore, the demand for […]
CONTINUOUS DISTRIBUTED INTERACTIVE APPLICATIONS WITH CLIENT ASSIGNMENT PROBLEM: ANALYSIS, ALGORITHMS, AND EVALUATION
Interactivity is characterized by the duration from the time when a participant issues an operation to the time when the effect of the operation is presented to the same participant or other participants. Interactivity is a primary performance measure for distributed interactive applications (DIAs) that enable participants at different locations to interact with each other […]
BESTPEER++: A NOVEL PEER-TO-PEER BASED DATA MANAGEMENT PLATFORM
The corporate network needs to scale up to sup- port thousands of participants, while the installation of a large-scale centralized data warehouse system entails nontrivial costs including huge hardware/software investments and high maintenance cost. In the real world, most companies are not keen to invest heavily on additional information systems until they can clearly see […]
- « Previous Page
- 1
- 2
- 3
- 4
- 5
- …
- 21
- Next Page »