Nabila Zrira

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Consuming and watching videos in YouTube is an integral part of our daily lives. Predicting videos popularity is of great importance for many services and application ranging from supporting the design and evaluation of a wide range of systems, including the targeted advertising to earn more money, ensure an effective search and recommendation systems, and(More)
Indoor environment classification, also known as indoor environment recognition, is a highly appreciated perceptual ability in mobile robots. In this paper, we present a novel approach which is centered on biologically inspired methods for recognition and representation of indoor environments. First, global visual features are extracted by using the GIST(More)
3D point cloud recognition is a challenging problem that is growing fast, especially with the development of acquisition cameras such as the Kinect that allows the generation of a lot of data to approximate an object model. Based on the types of features used to represent an object from multi-views, 3D object recognition approaches can be classified into(More)
We present in this paper a real-time method for visual categorization to do robot grasping. We describe an object database with SURF feature points which we quantify with the Kmeans clustering algorithm to make visual words. Then, we train a Support Vector Machine classifier having as entries the distribution of the bag of features extracted earlier.(More)
Outlier and anomaly detection are widely used in several fields of study such as social networks, statistics, and knowledge discovery. In social networks, it is useful to detect structural abnormalities which are different from the typical behavior of the social network in order to maintain the network security and privacy. In this paper, we suggest a new(More)
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