Taron, JoshuaParker, Matthew2016-08-232016-08-2320162016http://hdl.handle.net/11023/3216Architecture has long relied on optical devices to recalibrate vision towards previously concealed datasets. This thesis situates Algorithmic Observation (AO) as a tool within this lineage and explores its ability to invert architectures’ relationship to optical prostheses through the production of n-dimensional vectors. AO is tasked with sensing and making sense of the physical city, a process that relies on the production of algorithmically curated images. These images multiply and reanimate the image of the city provoking new optical regimes that situate aesthetics at the forefront of how architecture is conceived and constructed. This thesis explores a framework for extracting and mobilizing n-dimensional vectors towards the production of an architecture concerned not only with its physical materiality but with its digital footprint.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.ArchitectureAlgorithmic ObservationComputer VisionSIFTVisual AnomaliesN-dimensional VectorsSpeculative Ecologiesmaster thesis10.11575/PRISM/25544