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Multiple object detection, object tracking, lane tracking, and motion detection are the four crucial and difficult tasks in the Shadow robot. A dynamic background, clutter, occlusion, shadows, cluttering, noise, etc. make it difficult. The fundamental processes of a shadow robot's multi-camera video analytics include object detection, tracking, object matching across several cameras, and reidentification. Multiple object recognition and tracking of contents from resourceful city videos may be produced according to the suitability of society like Autonomous/Self-Driving vehicles, far-sighted clever inspection devices, traffic congestion administration devices, vehicle navigation, smart health management facilities, etc. Multiple object detection, object tracking, lane tracking and motion of moving objects are techniques used in computer vision and image processing. Several techniques are used to compare multiple consecutive frames from a movie to see whether any moving objects can be found. Results of the study show that the suggested technique may be used in areas such as object identification, motion detection, autonomous driving systems, and others.
"Multiple Object Detection, Object Tracking, Lane Tracking, and Motion Detection Shadow Robot Based on Computer Vision", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.838 - 845, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305133.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator