Video Sequence Learning and Recognition Via Dynamic Som
نویسندگان
چکیده
Information contained in the video sequences is crucial for an autonomous robot or a computer to learn and respond to its surrounding environment. In the past, robot vision is mainly concentrated on still image processing and small “image cube” processing [1]. Continuous video sequence learning and recognition is rarely addressed in the literature due to its high requirement on dynamic processing. In this paper, we propose a novel neural network structure called Dynamic Self-Organizing Map (DSOM) for video sequence processing. The proposed technique has been tested on real data sets, and the results validate its learning /recognition ability.
منابع مشابه
Action Change Detection in Video Based on HOG
Background and Objectives: Action recognition, as the processes of labeling an unknown action of a query video, is a challenging problem, due to the event complexity, variations in imaging conditions, and intra- and inter-individual action-variability. A number of solutions proposed to solve action recognition problem. Many of these frameworks suppose that each video sequence includes only one ...
متن کاملDetecting the Moving Object in Dynamic Backgrounds by using Fuzzy-Extreme
Moving object detection in dynamic background is the important features in video surveillance systems. Detecting the moving object using the SOM in video streams are not suitable for dynamic background and it requires complex computation to adjust the threshold values based on HSV. This paper proposes Fuzzy-Extreme Learning Machine (FELM) for detecting the object in dynamic backgrounds. The pro...
متن کاملHand Gesture Recognition based on SOM and ART
Gesture recognition is needed for a variety of applications such as human-computer interfaces, communication aids for the deaf, etc. In this paper, we present a SOMART system for the recognition of hand gestures. The sequence of a hand gesture is first projected into a 2-dimensional trajectory on a self-organizing feature map (SOM). Then the problem of recognizing hand gestures is transformed t...
متن کاملA Self-organizing Map Approach for Process Fault Diagnosis during Process Transitions
In this paper, we outline a self-organizing map (SOM) based approach to monitor process transitions. The framework integrates SOM with clustering and sequence comparison methods for plant wide monitoring and fault diagnosis. Process abnormality is detected through cluster analysis while syntactic pattern recognition technique and profile sequence comparison techniques render data based fault di...
متن کاملRecognition of Visual Events using Spatio-Temporal Information of the Video Signal
Recognition of visual events as a video analysis task has become popular in machine learning community. While the traditional approaches for detection of video events have been used for a long time, the recently evolved deep learning based methods have revolutionized this area. They have enabled event recognition systems to achieve detection rates which were not reachable by traditional approac...
متن کامل