We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, illumination and partial occlusion. The temporal continuity of the video within a shot is used to tr...

This paper presents four spatio-temporal wavelet decompositions for characterizing dynamic textures. The main goal of this work is to compare the influence of spatial and temporal variables in the wavelet decomposition scheme. Its novelty is to establish a comparison between the only existing method [11] and three other spatio-temporal decompositions. The four decomposition schemes are presente...

The potential value of human action recognition has led to it becoming one of the most active research subjects in computer vision. In this paper, we propose a novel method to automatically generate low-level spatio-temporal descriptors showing good performance, for high-level human-action recognition tasks. We address this as an optimization problem using genetic programming (GP), an evolution...

We propose a 3-step algorithm for the automatic detection of moving objects in video sequences using region-based active contours. First, we introduce a very full general framework for region-based active contours with a new Eulerian method to compute the evolution equation of the active contour from a criterion including both region-based and boundary-based terms. This framework can be easily ...

In the last decade, we observed a great interest in evaluation of local visual features in the domain of images. The aim is to provide researchers guidance when selecting the best approaches for new applications and data-sets. Most of the state-of-the-art features have been extended to the temporal domain to allow for video retrieval and categorization using similar techniques to those used for...

This paper presents a novel method for learning classes of temporal sequences using a bag-of-features approach. We define a temporal sequence as a bag of temporal features and show how this representation can be used for the recognition and segmentation of temporal events. A codebook of temporal descriptors, representing the local temporal texture, is automatically constructed from a set of sam...

Most of the existed action recognition methods mainly utilize spatio-temporal descriptors of single interest point ignoring their potential integral information, such as spatial distribution information. By combining local spatio-temporal feature and global positional distribution information (PDI) of interest points,a novel motion descriptor is proposed in this paper. The proposed method detec...

The basic reproduction number R0--the number of individuals directly infected by an infectious person in an otherwise susceptible population--is arguably the most widely used estimator of how severe an epidemic outbreak can be. This severity can be more directly measured as the fraction of people infected once the outbreak is over, Ω. In traditional mathematical epidemiology and common formulat...

In this paper we present an approach towards the classification of pitched and unpitched instruments in polyphonic audio. In particular, the presented study accounts for three aspects currently lacking in literature: model scalability to polyphonic data, model generalisation in respect to the number of instruments, and incorporation of perceptual information. Therefore, our goal is a unifying r...

Today, video surveillance systems produce thousands of terabytes of data. This source of information can be very valuable, as it contains spatio-temporal information about abnormal, similar or periodic activities. However, a search for certain situations or activities in unstructured large-scale video footage can be exhausting or even pointless. Searching surveillance video footage is extremely...