A fuzzy theoretic approach for video segmentation using syntactic features
01 Nov 2001-Pattern Recognition Letters (Elsevier Science Inc.)-Vol. 22, Iss: 13, pp 1359-1369
TL;DR: Experimental results have shown that the proposed scheme for fuzzification of the frame-to-frame property difference values using the Rayleigh distribution can detect changes reliably.
Abstract: This paper is concerned with the development of a fuzzy-logic-based framework for segmentation of video sequences. We have proposed a scheme for fuzzification of the frame-to-frame property difference values using the Rayleigh distribution. The difference values have been characterized by fuzzy terms like small, significant, large, etc. These terms have been used to design fuzzy rules for detecting abrupt changes and gradual changes. Fuzzy rules have provided a mechanism for integrating evidences based on different properties. The decompositional inference strategy has been used for fuzzy reasoning over the set of fuzzy rules. Gradual changes have been further classified as fade-in, fade-out and others (including dissolves, wipes, etc). Experimental results have shown that the proposed scheme can detect changes reliably.
••11 Jul 2021
TL;DR: In this article, a robust and computationally efficient deep learning-based framework was proposed to recognize real-world anomalies from the video, which uses a Fuzzy rule to summarize the video to scale the problem into fewer frames and the slow-fast neural network for classification.
Abstract: Anomalous events occur rarely and are challenging to model. Therefore, automatic recognition of abnormal activities in surveillance videos is a non-trivial task. Though with the availability of video datasets of abnormal activities, there has been some progress, recognition of abnormal activities in real-time with high confidence remains unsolved. Existing video-based anomaly detection techniques using traditional machine learning and deep-learning are compute-intensive and give low recognition accuracy. This paper presents a robust and computationally efficient deep learning-based framework to recognize different real-world anomalies from the video. The proposed scheme uses a Fuzzy rule to summarize the video to scale the problem into fewer frames and the slow-fast neural network for classification. Intuitively, the designed pipeline aims to solve two significant problems that arise with video classification; one is to reduce the redundant frames and avoid the computation of optical flow for a video that has a substantial computational requirement. The proposed scheme tested on the UCF-crime dataset and has achieved recognition accuracy of 53%.
01 Aug 1996
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Abstract: A fuzzy set is a class of objects with a continuum of grades of membership. Such a set is characterized by a membership (characteristic) function which assigns to each object a grade of membership ranging between zero and one. The notions of inclusion, union, intersection, complement, relation, convexity, etc., are extended to such sets, and various properties of these notions in the context of fuzzy sets are established. In particular, a separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
01 Jan 1978
TL;DR: This best-selling, easy to read book offers the most complete discussion on the theories and principles behind today's most advanced communications systems.
Abstract: This best-selling, easy to read book offers the most complete discussion on the theories and principles behind today's most advanced communications systems. Throughout, Haykin emphasizes the statistical underpinnings of communication theory in a complete and detailed manner. Readers are guided though topics ranging from pulse modulation and passband digital transmission to random processes and error-control coding. The fifth edition has also been revised to include an extensive treatment of digital communications.
TL;DR: In this article, a fuzzy logic is used to synthesize linguistic control protocol of a skilled operator for industrial plants, which has been applied to pilot scale plants as well as in practical situations.
Abstract: This paper describes an application of fuzzy logic in designing controllers for industrial plants. A fuzzy logic is used to synthesize linguistic control protocol of a skilled operator. The method has been applied to pilot scale plants as well as in practical situations. The merits of this method and its usefulness to control engineering are discussed. An avenue for further work in this area is described where the need is to go beyond a purely descriptive approach, and means for implementing a prescriptive or a self-organizing system are explored.
TL;DR: A twin-comparison approach has been developed to solve the problem of detecting transitions implemented by special effects, and a motion analysis algorithm is applied to determine whether an actual transition has occurred.
Abstract: Partitioning a video source into meaningful segments is an important step for video indexing. We present a comprehensive study of a partitioning system that detects segment boundaries. The system is based on a set of difference metrics and it measures the content changes between video frames. A twin-comparison approach has been developed to solve the problem of detecting transitions implemented by special effects. To eliminate the false interpretation of camera movements as transitions, a motion analysis algorithm is applied to determine whether an actual transition has occurred. A technique for determining the threshold for a difference metric and a multi-pass approach to improve the computation speed and accuracy have also been developed.