Bruno Macchiavello

Bruno Macchiavello

This book invites readers to see mathematics not just as formulas and rules, but as the deepest expression of human thought. It begins by exploring the timeless idea of mathematics as a universal language, contrasting its precision with the richness of natural speech. From the foundations of pure and applied mathematics to the revolutionary insights of Claude Shannon's information theory, the narrative shows how numbers, symbols, and structures have shaped science, technology, and communication. At the heart of the work lies the Binary Principle -- the idea that zero and one are not merely digits, but primitive building blocks of all mathematical reasoning. By treating absence and presence as fundamental units, the book reveals how complex theories and applications emerge from the simplest distinctions. This perspective makes mathematics more intuitive, more engaging, and more accessible, transforming how it can be taught and understood. Discover the Binary Principle: Mathematics as the True Universal Language. This book invites readers to see mathematics not just as formulas and rules, but as the deepest expression of human thought.

Bruno Macchiavello, Camilo Dorea, Edson M. Hung et al.

Free-viewpoint video conferencing allows a participant to observe the remote 3D scene from any freely chosen viewpoint. An intermediate virtual viewpoint image is commonly synthesized using two pairs of transmitted texture and depth maps from two neighboring captured viewpoints via depth-image-based rendering (DIBR). To maintain high quality of synthesized images, it is imperative to contain the adverse effects of network packet losses that may arise during texture and depth video transmission. Towards this end, we develop an integrated approach that exploits the representation redundancy inherent in the multiple streamed videos a voxel in the 3D scene visible to two captured views is sampled and coded twice in the two views. In particular, at the receiver we first develop an error concealment strategy that adaptively blends corresponding pixels in the two captured views during DIBR, so that pixels from the more reliable transmitted view are weighted more heavily. We then couple it with a sender-side optimization of reference picture selection (RPS) during real-time video coding, so that blocks containing samples of voxels that are visible in both views are more error-resiliently coded in one view only, given adaptive blending will erase errors in the other view. Further, synthesized view distortion sensitivities to texture versus depth errors are analyzed, so that relative importance of texture and depth code blocks can be computed for system-wide RPS optimization. Experimental results show that the proposed scheme can outperform the use of a traditional feedback channel by up to 0.82 dB on average at 8% packet loss rate, and by as much as 3 dB for particular frames.