This thesis presents a new approach to the visualization of audio files that simultaneously illustrates general audio properties and the component sounds that comprise a given input file. New audio segmentation and classification methods are reported that outperform existing methods. In order to visualize audio files, the audio is segmented (separated into component sounds) and then classified in order to select matching archetypal images or video that represent each audio segment and are used as templates for the visualization. Each segment's template image or video is then subjected to image processing filters that are driven by audio features. One visualization method reported represents heterogeneous audio files as a seamless image mosaic along a time axis where each component image in the mosaic maps directly to a discovered component sound. The second visualization method, video texture mosaics, builds on the ideas developed in time mosaics. A novel adaptive video texture generation method was created by using acoustic similarity detection to produce a resultant video texture that more accurately represents an audio file. Compared with existing visualization methods such as oscilloscopes and spectrograms, both approaches yield more accessible illustrations of audio files and are more suitable for casual and non expert users.

This thesis presents a new approach to the visualization of audio files that simultaneously illustrates general audio properties and the component sounds that comprise a given input file. New audio segmentation and classification methods are reported that outperform existing methods. In order to visualize audio files, the audio is segmented (separated into component sounds) and then classified in order to select matching archetypal images or video that represent each audio segment and are used as templates for the visualization. Each segment's template image or video is then subjected to image processing filters that are driven by audio features. One visualization method reported represents heterogeneous audio files as a seamless image mosaic along a time axis where each component image in the mosaic maps directly to a discovered component sound. The second visualization method, video texture mosaics, builds on the ideas developed in time mosaics. A novel adaptive video texture generation method was created by using acoustic similarity detection to produce a resultant video texture that more accurately represents an audio file. Compared with existing visualization methods such as oscilloscopes and spectrograms, both approaches yield more accessible illustrations of audio files and are more suitable for casual and non expert users.

<p>The progression of technical development has yielded practicable camera systems for the acquisition of so called depth maps, images with depth information. </p><p>Images and movies with depth information open the door for new types of applications in the area of computer graphics and vision. That implies that they will need to be processed in all increasing volumes.</p><p>Increased depth image processing puts forth the demand for a standardized data format for the exchange of image data with depth information, both still and animated. Software to convert acquired depth data to such videoformats is highly necessary. </p><p>This diploma thesis sheds light on many of the issues that come with this new task group. It spans from data acquisition over readily available software for the data encoding to possible future applications. </p><p>Further, a software architecture fulfilling all of the mentioned demands is presented. </p><p>The encoder is comprised of a collection of UNIX programs that generate MPEG Z/Alpha, an MPEG2 based video format. MPEG Z/Alpha contains beside MPEG2's standard data streams one extra data stream to store image depth information (and transparency). </p><p>The decoder suite, called TexMPEG, is a C library for the in-memory decompression of MPEG Z/Alpha. Much effort has been put into video decoder parallelization, and TexMPEG is now capable of decoding multiple video streams, not only in parallel internally, but also with inherent frame synchronization between parallely decoded MPEG videos.</p>

The progression of technical development has yielded practicable camera systems for the acquisition of so called depth maps, images with depth information. Images and movies with depth information open the door for new types of applications in the area of computer graphics and vision. That implies that they will need to be processed in all increasing volumes. Increased depth image processing puts forth the demand for a standardized data format for the exchange of image data with depth information, both still and animated. Software to convert acquired depth data to such videoformats is highly necessary. This diploma thesis sheds light on many of the issues that come with this new task group. It spans from data acquisition over readily available software for the data encoding to possible future applications. Further, a software architecture fulfilling all of the mentioned demands is presented. The encoder is comprised of a collection of UNIX programs that generate MPEG Z/Alpha, an MPEG2 based video format. MPEG Z/Alpha contains beside MPEG2's standard data streams one extra data stream to store image depth information (and transparency). The decoder suite, called TexMPEG, is a C library for the in-memory decompression of MPEG Z/Alpha. Much effort has been put into video decoder parallelization, and TexMPEG is now capable of decoding multiple video streams, not only in parallel internally, but also with inherent frame synchronization between parallely decoded MPEG videos.