The goal of this paper is to build robust human action recognition for real world surveillance videos. Local spatio-temporal features around interest points provide compact but descriptive representations for video analysis and motion recognition. Current approaches tend to extend spatial descriptions by adding a temporal component for the appearance descriptor, which only implicitly captures m...

In this thesis we present a system for automatic human tracking and activity recognition from video sequences. The problem of automated analysis of visual information in order to derive descriptors of high level human activities has intrigued computer vision community for decades and is considered to be largely unsolved. A part of this interest is derived from the vast range of applications in ...

Recent studies witness the success of Bag-of-Features (BoF) frameworks for video based human action recognition. The detection and description of local interest regions are two fundamental problems in BoF framework. In this paper, we propose a motion boundary based sampling strategy and spatialtemporal (3D) co-occurrence descriptors for action video representation and recognition. Our sampling ...

a robust and reliable quantitative structure-property relationship (qspr) study was established to forecast the melting points (mps)  of a diverse and long set including 250 drug-like compounds. based on the calculated descriptors by dragon software package, to detect homogeneities and to split the whole dataset into training and test sets, a principal component analysis (pca) approach was used...

We describe progress in matching shots which are images of the same 3D location in a film. The problem is hard because the camera viewpoint may change substantially between shots, with consequent changes in the imaged appearance of the scene due to foreshortening, scale changes, partial occlusion and lighting changes. We develop and compare two methods which achieve this task. In the first meth...

In this paper, we address the problem of motion recognition using event-based local motion representations. We assume that similar patterns of motion contain similar events with consistent motion across image sequences. Using this assumption, we formulate the problem of motion recognition as a matching of corresponding events in image sequences. To enable the matching, we present and evaluate a...

binary logistic regression (blr) has been developed as non-linear models to establish quantitative structure- activity relationships (qsar) between structural descriptors and biochemical activity of carbonic anhydrase inhibitors. using a training set consisted of 21 compounds with known ki values, the model was trained and tested to solve two-class problems as active or inactive on the basis of...

This paper resumes the results of a research conducted in a music production situation Therefore, it is more a final lab report, a prospective methodology then a scientific experience. The methodology we are presenting was developed as an answer to a musical problem raised by the Italian composer Marta Gentilucci. The problem was “how to extract a temporal structure from a vowel tremolo, on a t...

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we...

This paper presents a document structure for describing transportable, dynamic multimedia documents. Multimedia documents consist of a set of discrete data components that are joined together in time and space to present a user (or reader) with a single coordinated whole. Transportable documents are those in which the document structure can be accessed across system environments independently o...