Maximum Consensus Problem

Discover the essential insights of "Maximum Consensus Problem" by Tat-Jun Chin, published by Springer International Publishing AG in 2017. This informative paperback spans 178 pages and delves into the challenges posed by outlier-contaminated data in the field of computer vision. The book highlights the significance of the maximum consensus robust criterion, which enables accurate estimation of quantities from noisy and outlier-prone visual measurements. Ideal for researchers and practitioners alike, this work provides a comprehensive understanding of how to effectively handle data imperfections in computer vision applications. Enhance your knowledge and skills in this critical area with Tat-Jun Chin's expert guidance.