Journal ArticleDOI
Granulation, rough entropy and spatiotemporal moving object detection
Debarati Bhunia Chakraborty,B. Uma Shankar,Sankar K. Pal +2 more
- Vol. 13, Iss: 9, pp 4001-4009
TLDR
A new spatio-temporal segmentation approach for moving object(s) detection and tracking from a video sequence is described, which is more robust to noise and gradual illumination change, and superior to several related methods.Abstract:
A new spatio-temporal segmentation approach for moving object(s) detection and tracking from a video sequence is described. Spatial segmentation is carried out using rough entropy maximization, where we use the quad-tree decomposition, resulting in unequal image granulation which is closer to natural granulation. A three point estimation based on Beta Distribution is formulated for background estimation during temporal segmentation. Reconstruction and tracking of the object in the target frame is performed after combining the two segmentation outputs using its color and shift information. The algorithm is more robust to noise and gradual illumination change, because their presence is less likely to affect both its spatial and temporal segments inside the search window. The proposed methods for spatial and temporal segmentation are seen to be superior to several related methods. The accuracy of reconstruction has been significantly high.read more
Citations
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Journal ArticleDOI
Deep learning in multi-object detection and tracking: state of the art
TL;DR: In this article, the authors provide a comprehensive overview of object detection and tracking using deep learning (DL) networks and compare the performance of different object detectors and trackers, including the recent development in granulated DL models.
Journal ArticleDOI
Image thresholding segmentation method based on minimum square rough entropy
Bo Lei,Jiu-lun Fan +1 more
TL;DR: A new form of square rough entropy is defined to measure the roughness in an image, and the corresponding image thresholding segmentation algorithm is proposed, which has good properties and simple computation.
Journal ArticleDOI
Granulated RCNN and Multi-Class Deep SORT for Multi-Object Detection and Tracking
TL;DR: In this paper , two new models, namely granulated RCNN (G-RCNN) and multi-class deep SORT (MCD-SORT), were developed for object detection and tracking, respectively from videos.
Journal ArticleDOI
A real-time video surveillance system for traffic pre-events detection.
TL;DR: In this article, a conceptual framework is proposed for the development of a video surveillance-based system for improving road safety, based on the framework, a set of algorithms are developed which are capable of detecting various traffic pre-events from traffic videos, such as speed violation, one-way traffic, overtaking, illegal parking, and wrong drop-off location of passengers.
Journal ArticleDOI
Granular computing in model based abdominal organs detection
TL;DR: In this study a concept of implementing granular computing in the detection of anatomical structures in abdominal computed tomography (CT) scans is introduced and an automatic model-based approach has been developed to identify organ specific voxels of the liver, spleen and kidneys.
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