Real-time feature extraction from video stream data for stream ...

Real-time feature extraction from video stream data for stream ...

5.2. Creation of datasets

together in the right order (given by the ascending numbering of the segments), we obtain

a full video and audio data stream of one channel. The .m3u-file gets updated regularly,

whereby new elements get added and old elements get deleted. Hence the video stream

is infinite. In order to ensure that only registered users watch the television channels,

the .ts-files are AES-encrypted and have to be decrypted before putted together.

5.1.4. Stop Channel, logout and stop session

After all the desired data is received, the channel should be stopped, the user should

be logged out and the session should of course be terminated. This is done by three

easy POST-Requests; each of them not requiring any parameters. The request have to

be addressed to the URLs https://HOST/zapi/stop, to stop the channel, https:

//HOST/zapi/account/logout, to log out the user and https://HOST/zapi/

session/goodbye, to stop the session.

5.1.5. Error responses

In some cases the sent requests may be irregular or can not be processed by the server.

In these cases the server replies with an error response, providing the user with brief

information about the occurred problem. An example for such an error-response can be

found in figure 5.7.




Figure 5.7.: Example for an error-response

The error code can be looked up on the Zattoo website, providing the user with hints

how to fix the error.

5.2. Creation of datasets

In order to be able to evaluate the performance of the applied approaches for shot

boundary detection, anchorshot detection, and coffee capsule recognition, it is necessary

to have labeled data. Hence it is not possible to test the approaches on live video data

received over the ZAPI. Rather we need to have fixed video datasets: one containing the

video data of news shows and one for the coffee capsule recognition project.

For this purpose, we downloaded video files of news shows on the Internet respectively

recorded a video file containing data of different coffee capsules. Unfortunately neither

the RapidMiner Image Mining Extension (see section 3.5.2) nor the streams framework

(see section 3.5.3) offers the opportunity to read in MPEG video files directly: The

RapidMiner Image Mining Extension requires a folder containing JPEG images as its

input, whilst the MJpegImageStream implementation of the streams framework (see


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