Real-time and Retrospective Analysis of Video Streams and Still Image Collections using MPEG-7 Ganesh Gopalan, College of Oceanic and Atmospheric Sciences,

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Presentation transcript:

Real-time and Retrospective Analysis of Video Streams and Still Image Collections using MPEG-7 Ganesh Gopalan, College of Oceanic and Atmospheric Sciences, Oregon State University

Introduction HD video streams have potential to improve understanding of deep sea eco- systems However, volume and complexity associated with the HD streams and formats can be overwhelming Our approach: Use industry standards to transform video into a data type vs. treating it as viewing material

MPEG-7 Overview Multimedia content description interface Consists of low-level descriptors and high- level description schemes Low-level descriptors provide statistical information about the pixel values in content Description Schemes are used to represent semantic information

Low Level Descriptors Structures that describe content in terms of the distribution of edges, colors, textures, shapes and motion Descriptors extracted using MPEG-7 Experimental Model (XM) software The input is a still image or a frame from video The output is an XML description of the statistical information

Examples of Low Level Descriptors Edge Histogram Homogeneous Texture Color Layout Color Structure Motion Activity Descriptors are rotation and scaling invariant

Descriptor Extraction and Search Phase 1: descriptor XML for collection of frames/still images is generated and cached Phase 2: difference between query image descriptor from those values cached in phase one is computed The cache can be augmented with the descriptors from a new video or still image collection

Description Schemes Description Schemes attempt to model the reality behind the content Low level descriptors can be used to tag objects of interest; the tags are then used to construct a high level description A search can then be performed against the higher level description schemes

High Definition Video Search Engine Applied MPEG-7 to the development of an HD search engine Extracted descriptors for approximately 10,000 frames from 2.5 hours of high definition content Content provided by the University of Washington from “Visions 05 Cruise” Also applied to search for eddies in satellite image collections; super-cells in radar images

Application Architecture.NET Windows Forms front end with an embedded Windows Media Player SQL Server back-end Common Language Run-time Integration for development of stored procedures to manage MPEG-7 XML Procedures can be written in.NET languages rather than SQL

Creating a CLR Stored Procedure CREATE FUNCTION FindUsingVisualDescriptor nvarchar(256) ) RETURNS nvarchar(MAX) AS EXTERNAL NAME MPEG7Document.StoredProcedures.FindUsingVisual Descriptor; GO

Creating an HTTP Endpoint CREATE ENDPOINT MPEG7 STATE = Started AS HTTP ( SITE = ‘XXX.XXX.XX.XXX', PATH = '/MPEG7Endpoint', AUTHENTICATION = (BASIC), PORTS = (SSL), SSL_PORT = 444 ) FOR SOAP (WEBMETHOD 'FindUsingVisualDescriptor' (NAME = 'looking.dbo.FindUsingVisualDescriptor', FORMAT = ALL_RESULTS), …)

User Interface UI allows conversion of video into frames using ffmpeg Descriptors of choice are then generated for all frames Descriptors are persisted to the server

Retrospective Search A query image initiates the search The descriptor value for the given image is compared with those cached from the video frames or still images The top 100 frames that are closest to the query image are returned

Retrospective Search Example

Real-time Event Detection In this case, we have a set of known images that have objects of interest Descriptors of frames from a real-time stream are compared on a continuous basis with those in the “event library” When the difference in descriptor values is below a threshold, an event has been detected

Example of an Event

Reference Event

Use of Multi-Core Systems The descriptor extraction process can be made faster by taking advantage of multiple processors or cores The total number of frames can be divided up amongst the available processors Threads extract the descriptors concurrently to generate chunks of XML The threads then signal each other to combine the chunks into a single file with the descriptor XML

Challenges Shadows and other lighting issues can create false positives May be necessary to use multiple descriptors for classification Processing high definition video at 30fps is computationally intensive Scaling to a large number of images such as on the web presents a challenge

Conclusion MPEG-7 supports a rich framework for content-based searches through its low level descriptors Detected content can be tagged effectively using the high level description schemes that can be used to locate, search through and distribute content

Future Directions Need to explore ways to speed up descriptor extraction using GPUs or hybrid GPGPUs. Explore Cloud Services to implement video services – transcoding video on the fly for different devices, descriptor extraction using HPC clusters, streaming services Explore the Surface Computer as a UI

Acknowledgements We are thankful to Professor John Delaney from the University of Washington for providing the HD footage We are also thankful to the NSF funded LOOKING team for supporting this effort