Video based action recognition has been an active area of research in recent years. This is due to the many potential applications such as video surveillance, video content analysis, human computer interaction and video archiving. The ongoing trend of research deals with many complex action recognition problems such as appearance, pose and illumination variations but problem video quality is st...

Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data. Deep learning, although a breakthrough for image classification and showing promise for videos, has still not clearly superseded action recognition methods using hand-crafted features, even when training on m...

All current popular hand-crafted key-point detectors such as Harris corner, MSER, SIFT, SURF... rely on some specific pre-designed structures for the detection of corners, blobs, or junctions in an image. In this paper, a novel sparse coding based key-point detector which requires no particular predesigned structures is presented. The key-point detector is based on measuring the complexity leve...

This paper describes a machine learning approach to building an efficient, accurate and fast name spotting system. Finding names in free text is an important task in many text-based applications. Most previous approaches were based on hand-crafted modules encoding language and genre-specific knowledge. These approaches had at least two shortcomings: they required large amounts of time and exper...

Most of the crowd abnormal event detection methods rely on complex hand-crafted features to represent the crowd motion and appearance. Convolutional Neural Networks (CNN) have shown to be a powerful tool with excellent representational capacities, which can leverage the need for hand-crafted features. In this paper, we show that keeping track of the changes in the CNN feature across time can fa...

We use combinatorial optimisation to accumulate strokes into digits. The recognition hierarchy is novel in that it is not crafted to be a “good” representation scheme, but is generated from the repeated calculation of low-order central moments.

In the continental law system, it is appropriate for judges to find relevant laws and consider rules defined in them when dealing with legal cases. Therefore, recommending quickly accurately based on case content crucial improving efficiency of processing. There have been researched works recommender systems various fields, but few lucubrates that recommend statutes To best our knowledge, there...