The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared ...
Artur Loza, Fanglin Wang, Jie Yang, Lyudmila Mihay...
Segmentation of video objects from background is a popular computer vision problem and has many important applications. Most existing methods are either computationally expensive ...
Identifying handled objects, i.e. objects being manipulated by a user, is essential for recognizing the person’s activities. An egocentric camera as worn on the body enjoys many...
In this paper, an ontology-driven approach for the semantic analysis of video is proposed. This approach builds on an ontology infrastructure and in particular a multimedia ontolog...
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...