Machine Learning for Audio, Image and Video Analysis

Abstract

One of the most interesting technological phenomena in recent years is the diffusion of consumer electronic products with constantly increasing acquisition, storage and processing power. As an example, consider the evolution of digital cameras: the first models available in the market in the early nineties produced images composed of 1.6 million pixels (this is the meaning of the expression 1.6 megapixels), carried an onboard memory of 16megabytes, and had an average cost higher than 10,000 U.S. dollars. At the time this book is being written, the best models are close to or even above 8 megapixels, have internal memories of one gigabyte and they cost around 1,000 U.S. dollars. In other words, while resolution and memory capacity have been multiplied by around five and fifty, respectively, the price has been divided by more than ten. Similar trends can be observed in all other kinds of digital devices including videocameras, cellular phones, mp3 players, personal digital assistants (PDA), etc. As a result, large amounts of digital material are being accumulated and need to be managed effectively in order to avoid the problem of information overload.