VIDEO SEARCHING BY AUTOMATIC ANNOTATION

GROUP NUMBER : 16 - 113

INSIDEPROJECT PROPOSAL

Group Members ,

IT 13122942 Wickramasinghe K.U

IT 11150558 Ashangani S.K

IT 13115494 De Silva D.W.N

IT 13112424 Gamwara V.M

INTRODUCTION

INSIDE

What is video

Sequence of images to form a moving picture

Our Mission

Friendly, simple video searching using automatic annotation to provide an accurate result

RESEARCH PROBLEM

Available search engines only provide Keyword searching, Audio searching, Image searching.

Most videos are weakly labeled or have misleading names.

Less applications with automatic video annotation.

SOLUTION

“INSIDE” a smart semantic video searching application with automatic annotation which support easy, quick user friendly querying and return an accurate list of videos for the requesting query.

LITERATURE REVIEW

Image subtraction and histogram comparison, traditional video shot boundary detection techniques – video slicing

( reference : Video summarization by video structure analysis and graph optimization Shi Lu,Department of Computer Science and Engineering)

Object detection techniques: Appearance Based Methods, Geometry-Based Methods (reference: OBJECT RECOGNITION METHODS BASED ON TRANSFORMATION COVARIANT FEATURES Jiri Matasand Stepan Obdrzalek)

Key word searching vs Semantic searching (reference : https://www.searchenginejournal.com/seo-101-semantic-search-care/119760/)

OBJECTIVES

Allow semantic video searching by analyzing the structure and detecting content objects.

Classify videos automatically without user interaction.

User friendly

Accurate

METHODOLOGY WITH TOOLS AND

TECHNIQUES

Video structure analysis – Shot boundary detection and video slicing

Deep Learning - Tensorflow

Data set preparation

Textual searching - Semantic searching

SYSTEM OVERVIEW

FUNCTIONS OF MEMBERS

Member Components Task

De Silva D.W.N Video structure analysis Identify shot boundaries. Fragment video into shots.Fragment shot into frames.

Ashangani S.K Deep Learning Neural Network configurations

Gamwara V.M Data set preparation Creation manipulation of large data set to train the Neural Network

Wickramasinghe K.U Textual searching Take search query as an input and identify a relationship among the words, return the output

BENEFITS FOR USER

Accurate, Efficient search results.

Can be used at any time any where.

Can annotate video automatically.

COMMERCIAL VALUE Can be used as a tool and implement in search engines

Can be used to categorize videos without user interaction

Ability to rate videos according to their category (harmful)

Thank You