This paper presents a novel approach to implement estimation and recognition of human motion from uncalibrated monocular video sequences. As it is difficult to find a good motion description for humans, we propose a matching scheme based on a local descriptor and a global descriptor, to detect individual body parts and analyze the shape of the whole body as well. In a frame-by-frame process, bo...

In this paper we describe an action/interaction detection system based on improved dense trajectories [20], multiple visual descriptors and bag-of-features representation. Given that the actions/interactions are not mutual exclusive, we train a binary classifier for every predefined action/interaction. We rely on a non-overlapped temporal sliding window to enable the temporal localization. We h...

Annotation and retrieval tools for multimedia digital libraries have to cope with the complexity of multimedia content. In particular, when dealing with video content, annotation and retrieval tools have to use appropriate knowledge structures that can effectively relate high level concepts to low and mid level visual features and, at the same time, integrate temporal information which is cruci...

Ontologies are defined as the representation of the semantics of terms and their relationships. Traditionally, they consist of concepts, concept properties, and relationships between concepts, all expressed in linguistic terms. In order to support effectively video annotation and content-based retrieval the traditional linguistic ontologies should be extended to include structural video informa...

We address the issue of automatic video genre retrieval. We propose three categories of content descriptors, extracted at temporal, color and structural level. At temporal level, video content is described with visual rhythm, action content and amount of gradual transitions. Colors are globally described with statistics of color distribution, elementary hues, color properties and relationship. ...

A spatial simulation model was developed to predict temporal changes in land use patterns in a Piedmont county in Georgia. Five land use categories were included: urban, crop, abandoned cropland, pasture, and forest. Land use data were obtained from historical aerial photography and digitized into a matrix based on a 1 ha grid cell format. Transitions of cells from one state to another were dep...

This paper presents a novel framework for human action recognition based on sparse coding. We introduce an effective coding scheme to aggregate low-level descriptors into the super descriptor vector (SDV). In order to incorporate the spatio-temporal information, we propose a novel approach of super location vector (SLV) to model the space-time locations of local interest points in a much more c...

We present a new algorithm for segmenting a scene consisting of multiple moving dynamic textures. We model the spatial statistics of a dynamic texture with a set of second order Ising descriptors whose temporal evolution of is governed by an AutoRegressive eXogenous (ARX) model. Given this model, we cast the dynamic texture segmentation problem in a variational framework in which we minimize th...

BACKGROUND Mesial temporal lobe epilepsy (TLE) is a remediable epileptic syndrome. About 40% of patients continue to have seizures after standard temporal lobectomy. It has been suggested that some of these patients could actually suffer from a more complex epileptogenic network. Because a few papers have been dedicated to this topic, we decided to write an article updating this theme. METHOD...

Visual Place Recognition (VPR) is the task of matching current visual imagery from a camera to images stored in reference map environment. While initial VPR systems used simple direct image methods or hand-crafted features, recent work has focused on learning more powerful features and further improving performance through either some form sequential matcher / filter hierarchical process. In bo...