Human Behavior Analysis in Uncontrolled Environments can be categorized in two main challenges: 1) Feature extraction and 2) Behavior analysis from a set of corporal language vocabulary. In this work, we present our achievements characterizing some simple behaviors from visual data on different real applications and discuss our plan for future work: low level vocabulary definition from bag-of-g...

We describe a high level feature extraction system for video. Video sequences are modeled using Gaussian Mixture Models. We have used those models in the past to segment video sequences into 2D+time objects. The segmentation result has been used with great success in a compression scheme. In the present work, the Gaussian components of the model are considered to completely model the correspond...

In few-shot unsupervised domain adaptation (FS-UDA), most existing methods followed the learning (FSL) to leverage low-level local features (learned from conventional convolutional models, e.g., ResNet) for classification. However, goal of FS-UDA and FSL are relevant yet distinct, since aims classify samples in target rather than source domain. We found that insufficient FS-UDA, which could int...

in this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. the precision-recall measure and the correct classification rate of the k-nn classifier are used to evaluate retrieval and classification performances, respectively. the experimental results for a database of 1000 images from 10 different semantic gro...

A video‘s soundtrack is usually highly correlated to its content. Hence, audio-based techniques have recently emerged as a means for video concept detection complementary to visual analysis. Most state-of-the-art approaches rely on manual definition of predefined sound concepts such as “engine sounds”, “outdoor/indoor sounds”. These approaches come with three major drawbacks: manual definitions...

In this paper, first we describe rushes summarization system which is made this year for the TRECVID2008 BBC rushes task. Our aim this year is to build up base system using minimum information and to see how it works. In the second we will describe about our High-level feature extraction system briefly.

Identifying peer-review helpfulness is an important task for improving the quality of feedback received by students, as well as for helping students write better reviews. As we tailor standard product review analysis techniques to our peer-review domain, we notice that peerreview helpfulness differs not only between students and experts but also between types of experts. In this paper, we inves...

This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human ob...