Simultaneous localization and mapping (SLAM) has attracted considerable research interest from the robotics and computer-vision communities for >30 years. With steady and progressive efforts being made, modern SLAM systems allow robust and online applications in real-world scenes. We examined the evolution of this powerful perception tool in detail and noticed that the insights concerning incremental computation and temporal guidance are persistently retained. Herein, we denote this temporal continuity as a flow basis and present for the first time a survey that specifically focuses on the flow-based nature, ranging from geometric computation to the emerging learning techniques. We start by reviewing two essential stages for geometric computation, presenting the de facto standard pipeline and problem formulation, along with the utilization of temporal cues. The recently emerging techniques are then summarized, covering a wide range of areas, such as learning techniques, sensor fusion, and continuous-time trajectory modeling. This survey aims at arousing public attention on how robust SLAM systems benefit from a continuously observing nature, as well as the topics worthy of further investigation for better utilizing the temporal cues.

Crossing is a fundamental paradigm for target selection in human-computer interaction systems. This paradigm was first introduced to virtual reality (VR) interactions by Tu et al., who investigated its performance in comparison to pointing, and concluded that crossing is generally no less effective than pointing and has unique advantages. However, owing to the characteristics of VR interactions, there are still many factors to consider when applying crossing to a VR environment. Thus, this review summarizes the main techniques for object selection in VR and crossing-related studies. Then, factors that may affect crossing interactions are analyzed from the perspectives of the input space and visual space. The aim of this study is to provide a reference for future studies on target selection based on the crossing paradigm in virtual reality.