Mode decision for the H.264/AVC video coding standard

H.264/AVC video coding standard gives us a very promising future for the field of video broadcasting and communication because of its high coding efficiency compared with other older video coding standards. However, high coding efficiency also carries high computational complexity. Fast motion estimation and fast mode decision are two very useful techniques which can significantly reduce computational complexity. This thesis focuses on the field of fast mode decision. The goal of this thesis is that for very similar RD performance compared with H.264/AVC video coding standard, we aim to find new fast mode decision techniques which can afford significant time savings. [Continues.

Object Tracking

Object tracking consists in estimation of trajectory of moving objects in the sequence of images. Automation of the computer object tracking is a difficult task. Dynamics of multiple parameters changes representing features and motion of the objects, and temporary partial or full occlusion of the tracked objects have to be considered. This monograph presents the development of object tracking algorithms, methods and systems. Both, state of the art of object tracking methods and also the new trends in research are described in this book. Fourteen chapters are split into two sections. Section 1 presents new theoretical ideas whereas Section 2 presents real-life applications. Despite the variety of topics contained in this monograph it constitutes a consisted knowledge in the field of computer object tracking. The intention of editor was to follow up the very quick progress in the developing of methods as well as extension of the application

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world

Current video compression algorithms: Comparisons, optimizations, and improvements

Compression algorithms have evolved significantly in recent years. Audio, still image, and video can be compressed significantly by taking advantage of the natural redundancies that occur within them. Video compression in particular has made significant advances. MPEG-1 and MPEG-2, two of the major video compression standards, allowed video to be compressed at very low bit rates compared to the original video. The compression ratio for video that is perceptually lossless (losses can\u27t be visually perceived) can even be as high as 40 or 50 to 1 for certain videos. Videos with a small degradation in quality can be compressed at 100 to 1 or more; Although the MPEG standards provided low bit rate compression, even higher quality compression is required for efficient transmission over limited bandwidth networks, wireless networks, and broadcast mediums. Significant gains have been made over the current MPEG-2 standard in a newly developed standard called the Advanced Video Coder, also known as H.264 and MPEG-4 part 10. (Abstract shortened by UMI.)