Open AccessIntelligent Crowd Counting System with Gender Classification
Author(s) -
Sheshang Degadwala,
Pragnya Kulkarni,
Mansi Patel,
Kesha Bhatt,
Dharvi Soni
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit2062140
Subject(s) - swarm behaviour , computer science , profiling (computer programming) , consistency (knowledge bases) , identification (biology) , artificial intelligence , task (project management) , computer vision , machine learning , pattern recognition (psychology) , engineering , botany , systems engineering , biology , operating system
Evaluating the quantity of individuals in exceptionally bunched swarm scenes is an amazingly testing task because of genuine impediment and non-consistency dispersion in one group picture. Human Counting innovation can be summed up into two sorts of writing: identification strategies and tallying techniques. Conventional methodologies for swarm tallying from pictures depended available made portrayals to remove low-level highlights. These highlights were then mapped for checking or creating thickness maps by means of different tallying procedures. The identification-based model commonly utilizes sliding window-based recognition calculations to include individuals in a picture. This Project likewise correlation of various sex grouping strategies and utilization of various racial highlights, for example, eyes, nose, and mouth, and so on for Gender orientation characterization its applications in numerous regions like observing, reconnaissance, and business profiling, and human-PC cooperation video order assignments.