Book ChapterDOI
A Low Cost Moving Object Detection Method Using Boundary Tracking
Soharab Hossain Shaikh,Nabendu Chaki +1 more
- pp 127-136
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TLDR
This paper proposes a new method for moving object detection from video sequences by performing frame-boundary tracking and active-window processing leading to improved performance with respect to computation time and amount of memory requirements.Abstract:
Moving object detection techniques have been studied extensively for such purposes as video content analysis as well as for remote surveillance. Video surveillance systems rely on the ability to detect moving objects in the video stream which is a relevant information extraction step in a wide range of computer vision applications. There are many ways to track the moving object. Most of them use the frame differences to analyze the moving object and obtain object boundary. This may be quite resource hungry in the sense that such approaches require a large space and a lot of time for processing. This paper proposes a new method for moving object detection from video sequences by performing frame-boundary tracking and active-window processing leading to improved performance with respect to computation time and amount of memory requirements. A stationary camera with static background is assumed.read more
Citations
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Proceedings ArticleDOI
Recognition of object orientation from images
TL;DR: This paper proposes a new method for detection of orientation of a small vehicle from eight different orientations with respect to a stationery camera based on extracting features of a car object in terms of boundary description known as the signature.
Book ChapterDOI
On Generation of Silhouette of Moving Objects from Video
TL;DR: A novel technique for extracting human silhouette from video in real time using frame differencing technique followed by a number of steps for extraction of the human silhouette is proposed.
Proceedings ArticleDOI
On recognition of human orientation with respect to a static camera
TL;DR: A method for detection of orientation of a human being from four different orientations with respect to a static camera and classification has been performed using the dissimilarity value as a metric.
Journal Article
Moving Object Tracking From A Video Sequence Using Bounding Box Method
TL;DR: The object tracking from a video sequence that contains moving objects is a critical task in real world applications and the proposed moving object tracking algorithm in which the moving object region can be extracted completely is considered.
References
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Journal ArticleDOI
Detecting moving objects, ghosts, and shadows in video streams
TL;DR: A general-purpose method is proposed that combines statistical assumptions with the object-level knowledge of moving objects, apparent objects (ghosts), and shadows acquired in the processing of the previous frames to improve object segmentation and background update.
Journal ArticleDOI
Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art
TL;DR: This paper surveys many existing schemes in the literature of background removal, surveying the common pre-processing algorithms used in different situations, presenting different background models, and the most commonly used ways to update such models and how they can be initialized.
Journal ArticleDOI
Performance evaluation of object detection algorithms for video surveillance
TL;DR: Novel methods to evaluate the performance of object detection algorithms in video sequences are proposed and segmentation algorithms recently proposed are evaluated in order to assess how well they can detect moving regions in an outdoor scene in fixed-camera situations.
Journal ArticleDOI
Shadow detection for moving objects based on texture analysis
Alessandro Leone,Cosimo Distante +1 more
TL;DR: In this work, a new approach to describe textural information in terms of redundant systems of functions is suggested, designed to be unaffected by scene type, background type or light conditions.
Proceedings ArticleDOI
A Contour-Based Moving Object Detection and Tracking
M. Yokoyama,Tomaso Poggio +1 more
TL;DR: A fast and robust approach to the detection and tracking of moving objects based on using lines computed by a gradient-based optical flow and an edge detector and each tracked object has a state for handling occlusion and interference.