ACTION RECOGNITION USING FEATURE TRANSFORM DESCRIPTOR FROM MINED DENSE SPATIO TEMPORAL

Action recognition in video sequence has been a major challenging research area for number of years. Apriori algorithm and SIFT descriptor based approach for action recognition is proposed in this paper. Here, two phases can be carried out for accurate and updating of action recognition. In the first phase, the input should be the video sequence. For preprocessing the sequences frame can be formatted by background modeling for every successive frame. After modeling the background, the corners are detected for every frame and compound features are extracted. Data mining is performed by using Apriori algorithm as well as with the help of compound features extraction the action can be segregated in this video sequence. In the second phase, the same process is performed as well as analysis for new input frame and new pattern are updated for perfect recognition process. Due to Apriori algorithm, the processing delay is reduced and accuracy is improved.

Using a maze task to track lexical and sentence processing

A word maze consists of a sequence of frames, each containing two alternatives. Subjects are required to select one of those alternatives according to some criterion defined by the experimenter. This simple technique can be used to investigate a wide range of issues. For example, if one alternative is a word and the other is a nonword, the subject may be required to press a key to indicate where the word is. This provides an interesting variant of the lexical decision task, since the difficulty of the lexical discrimination can be manipulated on a trial-by-trial basis by varying the properties of the nonword alternative. On the other hand, a version of a self-paced reading task is created if each successive frame contains a word that can continue a sentence, and the subject is required to identify which word that is. Once again, by manipulating the properties of the incorrect alternative one may be able to control the mode of processing adopted by the subject. Although this is a highly artificial form of reading, it does allow one to study the sentence processing under more tightly controlled conditions.