Hi Rupert,
Thanks for your instructions! I studied the 2 ontologies you pointed out.
They are useful for common media/fragment annotations, but maybe not enough
for face detection? For example, shall we define our own new face detection
("fd" as prefix) ontology properties like "fd:hasFaceImage",
"fd:hasFaceVideoSegment"? Or are there existing face detection ontologies
to reuse?
Also, here are my further questions about the 3 possible engines you
mentioned:
1) scene detection: to set detected faces in a context. This could be used
to group different faces found within the same scene)
- What is a "scene"? Is it a frame/image or video segment? What is a
"context"?
2) face detection. Video segments showing a face could be marked with
MediaFragments URIs so the clients can easily play back the annotated
section in the browser.
- I can understand it. The input of the engine is a video, with the output
of MediaFragments URIs marking the video segments showing a face. Do you
mean showing the same face? What if a video segment contain multiple faces?
Will the video segments be extracted and stored as Content parts (Blobs) of
the input video?
3) extraction of images showing detected faces. This would be nice for
Clients as they can easily show detected faces to users.
- As is discussed in the previous e-mail, the input of the engine is a
image, with the output of extracted images of the detected faces. For a
video, we firstly need another FrameExtractionEngine to extract all the
frames as images, and then apply the face extraction engine for each frame.
This could be clear in terms of separation of functionality. But may be
poor in performance? Because there're so many frames even for small video.
OpenIMAJ adopts VideoDisplayListener mechanism, so that the frames of the
video can be precessed one by one in a flow [1]. What's your opinion?
Yours, truly
Jenny
[1] http://www.openimaj.org/tutorial/finding-faces.html
2014-03-05 13:30 GMT+08:00 Rupert Westenthaler <
rupert.westentha...@gmail.com>:
> Hi Jenny
>
> Thanks for your interest in Stanbol. I will try to give you some more
> information
> on the topic you are interested in. See my comments inline.
>
> On Tue, Mar 4, 2014 at 3:35 PM, Zhu Qiuxiang <jenny.qiuxi...@gmail.com>
> wrote:
> > Hi all,
> >
> > My full name is Qiuxiang Zhu (you can call me Jenny for short), who is a
> > Chinese student interested in participating GSoC 2014. In recent years,
> > I've been working on semantic web related projects, most of which are
> small
> > student projects funded by my university, with a big project of finance
> > knowledge base (RDF/OWL) development from my tutor. I'm quite experienced
> > with RDF, Topbraid Composer, Jena, SPARQL and Linked Data.
> >
> > Apache Stabol attracts me because it adopts semantic technologies for
> > content management, especially the Enhancer component to process semantic
> > data in a chain. I've read the related documents [1]. I can also
> understand
> > the source code of the Tika Engine [2].
> >
> > In GSoC 2014, I'd like to work on a similar engine of "Face Detection
> > Engine based on OpenIMAJ" [3] (STANBOL-1006) which also deals with Blobs.
> > Could you please tell me more about the details of the project? Here're
> my
> > questions:
> >
> > 1) The input of the Face Detection Engine can be a ContentItem containing
> > the original images. Are the extracted face images registered with
> > predefined URIs as Content parts (Blobs) in the ContentItem?
>
> In Stanbol Content is accessible as Blobs. The Blob provides the
> Content-Type
> and an InputStream to read the data. Both images and videos are possible
> inputs for a Face Detection Engine
>
> >
> > 2) What metadata can be enhanced for Face Detection Engine? Are there any
> > Face Detection related ontologies to be reused?
>
> Extending the Stanbol Enhancement Structure for Image and Video Annotations
> is covered by STANBOL-1005. There are several existing ontologies and even
> Recommendations like MediaFragments [1], the ontology for Media Resources
> [2]
> that should be considered.
>
>
> [1] http://www.w3.org/TR/media-frags/
> [2] http://www.w3.org/TR/mediaont-10/
>
> >
> > 3) How to deal with videos? It looks like that we should firstly (1)
> > extract images/frames from the videos, and then (2) apply Face Detection
> > Engine for face recognition. Shall we separate (1) from (2), to make a
> > Video Frame Extraction Engine?
>
> AFAIK OpenIMAJ provides all the required functionality. Separation of
> functionality in different engines is a good thing as it allows users more
> flexibility of configuring chains.
>
> I see a lot of possible engines
>
> * scene detection: to set detected faces in a context. This could be
> used to group different faces found within the same scene)
> * face detection. Video segments showing a face could be marked with
> MediaFragments URIs so the clients can easily play back the annotated
> section in the browser.
> * extraction of images showing detected faces. This would be nice for
> Clients as they can easily show detected faces to users
>
>
> best
> Rupert
>
> >
> >
> > Yours truly,
> > Jenny
> >
> >
> >
> >
> > [1] http://stanbol.apache.org/docs/trunk/components/enhancer/
> > [2]
> >
> https://svn.apache.org/repos/asf/stanbol/trunk/enhancement-engines/tika/src/main/java/org/apache/stanbol/enhancer/engines/tika/TikaEngine.java
> > [3] https://issues.apache.org/jira/browse/STANBOL-1006
>
>
>
> --
> | Rupert Westenthaler rupert.westentha...@gmail.com
> | Bodenlehenstraße 11 ++43-699-11108907
> | A-5500 Bischofshofen
>
