In this paper we propose a method for efficient extraction of human silhouette from video sequences. The proposed approach includes background elimination, edge detection, region filling and noise removal using morphological operations to estimate the silhouette of an image. To the best of our knowledge our proposed approach for silhouette extraction involving background elimination and edge detection is first of its kind. We have applied our proposed technique on Weizmann (standard) dataset and compared the results with the most recent related research work. The comparison results in terms of statistical measures like precision, recall and F-measure clearly show the supremacy of our method and thus justify its novelty. © Springer Nature Singapore Pte Ltd. 2017.

AMLAN CHAKRABORTY

GENERAL

A RAYCHAUDHURI

S MAITY

D BHATTACHARJEE

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

A novel approach for human silhouette extraction from video data

Advances in Intelligent Systems and Computing

This chapter presents a novel background subtraction technique for detecting moving objects from video under dynamic background conditions. The presented methodology is a simple and low-cost solution for modeling and updating background during a background subtraction process. Comparative performance analysis with other state-of-the-art methods on benchmark data-set shows the effectiveness of the proposed method. The objective of the research is not to claim that the proposed method yields the best result in terms of accuracy; rather the main novelty is in its low computational cost. However, in spite of being less computation-intensive, comparative analysis reveals that the new method produces quite competitive results as compared to other methods. The proposed method would be useful particularly for applications in resource constrained environments by virtue of its low computation time and storage requirements. © The Author(s) 2014.

SpringerBriefs in Computer Science

Moving object detection: A new approach

Object classification from video is a well known topic of research in the context of computer vision. Video processing for the purpose of real time object classification and action recognition has great importance in building an intelligent surveillance system. This paper proposes a novel technique for extracting human silhouette from video in real time. Identification of the moving human objects is performed first using frame differencing technique followed by a number of steps for extraction of the human silhouette. The proposed method has been tested on a good number of videos having varying textured background with noise related to illumination change. The proposed method can also be applied for extraction of silhouettes of other types of animate and inanimate moving objects from a video with the view of object classification and recognition. The experimental results as documented in the paper establish the effectiveness of the proposed method. © 2013 Springer.

Lecture Notes in Electrical Engineering

On generation of silhouette of moving objects from video

International Journal of Computer Theory and Engineering

Accurate Silhouette Extraction of a Person in Video Data by Shadow Evaluation

2013 IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS)

Computer Analysis of Images and Patterns Lecture Notes in Computer Science

A New Pixel-Based Quality Measure for Segmentation Algorithms Integrating Precision, Recall and Specificity

Journal	Data powered by TypesetAdvances in Intelligent Systems and Computing
Publisher	Data powered by TypesetSpringer Verlag
ISSN	2194-5357