The complexity of multimedia contents is significantly increasing in the current digital world.
This yields an exigent demand for develo** highly effective retrieval systems to satisfy …

In this paper, we propose a novel benchmark for evaluating local image descriptors. We
demonstrate that the existing datasets and evaluation protocols do not specify …

Video coding, which targets to compress and reconstruct the whole frame, and feature
compression, which only preserves and transmits the most critical information, stand at two …

This paper presents a content-based image retrieval technique that focuses on extraction
and reduction in multiple features. To obtain multi-level decomposition of the image by …

SIFT is a classical hand-crafted, histogram-based descriptor that has deeply influenced
research on image matching for more than a decade. In this paper, a critical review of the …

Detecting text in natural images is an important prerequisite. In this paper, we propose a
novel text detection algorithm, which employs edge-enhanced Maximally Stable Extremal …

SIFT-like local feature descriptors are ubiquitously employed in computer vision applications
such as content-based retrieval, video analysis, copy detection, object recognition, photo …

We introduce the term cosegmentation which denotes the task of segmenting
simultaneously the common parts of an image pair. A generative model for cosegmentation …

In the 17 years since the first edition of Fundamentals of Multimedia, the field and
applications of multimedia have flourished and are undergoing evermore rapid growth and …

We introduce a simple modification of local image descriptors, such as SIFT, based on
pooling gradient orientations across different domain sizes, in addition to spatial locations …