Precise deformation surveying is essential for ensuring safety and sustainable development in densely populated cities. Synthetic aperture radar interferometry (InSAR) is a technique well suited for large-scale deformation measurement. It is widely applied in monitoring geological disasters such as earthquakes, landslides, and volcanoes. However, it faces challenges when used to monitor urban infrastructure, which requires higher precision and more details. To overcome these challenges, we introduce an innovative, object-oriented multitemporal InSAR (Obj-InSAR) framework. Compared with state-of-the-art InSAR methods, Obj-InSAR shifts the basic processing unit from pixel to object. This allows the use of additional information provided by the object/segment to enable detailed and precise results, as required in urban scenarios. In this framework, a novel object-based plug-in network is designed to establish an impressively dense network for parameters solving. Additionally, a new object-based adjustment procedure through 3-D point cloud alignment is proposed to accurately determine the location of InSAR scatterers and guide network construction. As a result, our approach produces a more detailed, accurate and precisely geolocated 4-D infrastructure point cloud than conventional pixel-oriented frameworks, enabling effective monitoring of urban deformation. A case study confirms the usefulness and adaptability of this approach in urban SAR interferometry. These advancements will contribute to the development of time-series InSAR technology in the new era, enhance the capability of monitoring complex urban deformation in high-density cities, and serve urban safety operations and sustainable economic development.