In this work, deep convolutional neural networks are used to automate the process of feature extraction from CCTV images. The extracted features serve as a strong basis for a variety of object recognition tasks and are used to address a tracking problem. The approach is to match the extracted features of individual detections in subsequent frames, hence creating a correspondence of detections a...

We present a watermarking procedure to embed copyright protection into digital video. Our watermarking procedure is scene-based and video dependent. It directly exploits spatial masking, frequency masking, and temporal properties to embed an invisible and robust watermark. The watermark consists of static and dynamic temporal components that are generated from a temporal wavelet transform of th...

In drawing a figure, hemispatial neglect patients typically produce an adequate representation of parts on the right of the figure while omitting significant features on the left. This contralateral neglect is influenced by multiple spatial reference frames and by the hierarchical structure of the object(s) in the figure. The current work presents a computational characterization of the interac...

We introduce a watermarking procedure to embed copyright protection into digital video. Our video dependent watermarking procedure directly exploits masking and temporal properties to embed an invisible and robust watermark. The watermark consists of static and dynamic temporal components that are generated from a temporal wavelet transform of the video scenes. To generate the watermark, the re...

In this paper, we present a new semantics for the well-known normal system of modal logic K based on the notion of convergence spaces. The purpose is to use convergence spaces to model and reason about systems with both discrete and continuous states, so-called hybrid state spaces. K is sound and complete with respect to the class of convergence space models, and we show that Kripke frames and ...

In linguistics, a study of the relation between word and meaning is called semantics. Semantics is a term for referring to study the meaning of elements of a language, particularly to study the real context of sentences and phrases of a language. The meaning of ‘recitation’ and ‘chanting’ in terms of Quranic, Hadith and idiomatic applications will be identified in this p...

This paper presents a framework for background detection in video. Key frames are extracted to capture background change in video and to reduce the magnitude of the data. Then we analyze the content of the key frames to determine whether there is interesting background in them. Key frames are extracted with a time-constrained clustering algorithm. Background detection in a key frame is done wit...

We present a novel generative model for transformation invariant data clustering, with the emphasis on video clustering and summarization. We model the data as the mixture of transformed exemplars. We include in the model the most common and realistic transformations in video data: camera motion, cropping, change in scale and light. The learning procedure automatically clusters video frames int...

Video scene change detection has great importance of managing and analyzing large amount of videos. Traditionally this technique used for indexing, segmenting and categorizing different types of videos. Very few works addressed to classify obscene using scene change detection method. In this research we proposed a simple approach for sensing objectionable videos by observing scene changes into ...

This talk is a contribution towards the project of developing discrete representability for the algebraic semantics of various non-classical logics. Discrete duality is a type of duality where a class of abstract relational systems is a dual counterpart to a class of algebras. These relational systems are referred to as ‘frames’ following the terminology of non-classical logics. There is no top...