EXPLOITING MULTI-CAMERA CONSTRAINTS WITHIN BUNDLE BLOCK ADJUSTMENT: AN EXPERIMENTAL COMPARISON

The growing deployment of multi-head camera systems encouraged the emergence of specific processing algorithms, able to face the challenges posed by slanted view geometry. Such multi-camera systems are rigidly tied by their manufacturers hence the exploitation of this internal constraint should be further exploited. Several approaches have been proposed to deal with orientation constraints, with the aim of reducing the number of unknowns, computational time and possibly improve the accuracy. In this paper we compare the results provided by publicly available implementations in order to further investigate the advantages of enforcing relative orientation constraints for aerial and terrestrial triangulation of multi-head camera systems. Data from a Leica CityMapper and a Stereopolis-Ladybug are considered, reporting how constrained solution can improve accuracy with respect to traditional (unconstrained) bundle block adjustment solutions.

Extremum Principles

This chapter derives the energy minimum principle from the entropy maximum principle. It postulates and consider the consequences of extensivity. From this are further derived minimum principles for the Helmholtz free energy, enthalpy, and Gibbs free energy. Because of its importance in engineering, exergy is also introduced, and the exergy minimum principle is justified. Analogously to these minimum principles, maximum principles can be derived for the Massieu functions from the entropy maximum principle. For the analysis of the entropy maximum principle, we isolated a composite system and released an internal constraint. Since the composite system was isolated, its total energy remained constant. The composite system went to the most probable macroscopic state after release of the internal constraint, and the total entropy went to its maximum.

Constraints and Motivators: A New Model to Explain Sport Consumer Behavior

This study focused on developing a model to explain relationships among constraints, motivators, and attendance, and empirically test the proposed model within the spectator sport context. The proposed model explained 34% of variance in Attendance. Results showed that Attachment to the Team, an internal motivator, entered first and explained approximately 21% of the variance in attendance. Lack of Success, an internal constraint, entered next and explained almost 10% additional variance. Leisure Alternatives, an external constraint entered next and explained an additional 3%. The ability to properly evaluate constraints and motivators gives sport marketers the opportunity to more effectively serve existing fans, as well as attract new fans.