Never before in history data has been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data becomes increasingly difficult. Information vi...
Searching and managing large archives of visual data, such as images and video, is made hard by the lack of proper integration between the visual aspects of the problem (image pro...
This paper presents a framework for directly addressing issues arising from self-occlusions and ambiguities due to the lack of depth information in vector-based representations. V...
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Abstract. Visual data
ow environments are ideally suited for modeling digital signal processing (DSP) systems, as many DSP algorithms are most naturally specied by signal
ow gra...
James Hwang, Brent Milne, Nabeel Shirazi, Jeffrey ...
In this paper, a method for inferring 3D structure information based on both range and visual data is proposed. Data fusion is achieved by validating assumptions formed according ...
Haris Baltzakis, Antonis A. Argyros, Panos E. Trah...
We investigate the implications of a unified spatiotemporal-chromatic basis for compression and reconstruction of image sequences. Different adaptive methods (PCA and ICA) are app...
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
We address the problem of detecting irregularities in visual data, e.g., detecting suspicious behaviors in video sequences, or identifying salient patterns in images. The term &qu...
We propose a principled approach to summarization of visual data (images or video) based on optimization of a well-defined similarity measure. The problem we consider is re-target...
Denis Simakov, Yaron Caspi, Eli Shechtman, Michal ...