Computer Vision and Image Understanding

Video sharing websites have recently become a tremendous video source, which is easily accessible without any costs. This has encouraged researchers in the action recognition field to construct action database exploiting Web sources. However Web sources ...

The ever increasing Internet image collection densely samples the real world objects, scenes, etc. and is commonly accompanied with multiple metadata such as textual descriptions and user comments. Such image data has potential to serve as a knowledge ...

Many research have been focusing on how to match the textual query with visual images and their surrounding texts or tags for Web image search. The returned results are often unsatisfactory due to their deviation from user intentions, particularly for ...

In the real world, people often have a habit tending to pay more attention to some things usually noteworthy, while ignore others. This phenomenon is associated with the top-down attention. Modeling this kind of attention has recently raised many ...

Sparse coding represents a signal sparsely by using an overcomplete dictionary, and obtains promising performance in practical computer vision applications, especially for signal restoration tasks such as image denoising and image inpainting. In recent ...

In this paper, we propose a constrained optimization approach to improving both the robustness and accuracy of kernel tracking which is appropriate for real-time video surveillance due to its low computational load. Typical tracking with histogram-wise ...

This paper presents a robust video stabilization method by solving a novel formulation for the camera motion estimation. We introduce spatio-temporal weighting on local patches in optimization formulation, which enables one-step direct estimation ...

The registration of multiple 3D structures in order to obtain a full-side representation of a scene is a long-time studied subject. Even if the multiple pairwise registrations are almost correct, usually the concatenation of them along a cycle produces ...

We present a novel keyframe-based global localization method for markerless real-time camera tracking. Our system contains an offline module to select features from a group of reference images and an online module to match them to the input live video ...

This article presents a unified framework for detecting, segmenting and tracking unknown objects in everyday scenes, allowing for inspection of object hypotheses during interaction over time. A heterogeneous scene representation is proposed, with ...

Local feature based object tracking approaches have been promising in solving the tracking problems such as occlusions and illumination variations. However, existing approaches typically model feature variations using prototypes, and this discrete ...

This paper presents a novel algorithm for medial surfaces extraction that is based on the density-corrected Hamiltonian analysis of Torsello and Hancock [1]. In order to cope with the exponential growth of the number of voxels, we compute a first coarse ...

With millions of users and billions of photos, web-scale face recognition is a challenging task that demands speed, accuracy, and scalability. Most current approaches do not address and do not scale well to Internet-sized scenarios such as tagging ...

We present a novel approach for robust localization of multiple people observed using a set of static cameras. We use this location information to generate a visualization of the virtual offside line in soccer games. To compute the position of the ...

Standard wildfire smoke detection systems detect fires using remote cameras located at observation posts. Images from the cameras are analyzed using standard computer vision techniques, and human intervention is required only in situations in which the ...

Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust. In this paper the 'Chess-board ...

We propose a new joint view-identity manifold (JVIM) for multi-view and multi-target shape modeling that is well-suited for automated target tracking and recognition (ATR) in infrared imagery. As a shape generative model, JVIM features a novel manifold ...