Flow visualization is a vital component in the workflow of studying computational fluid dynamic simulations. Integral curves or streamlines are one of the most commonly used techniques to visualize flow fields and selecting a good set of streamlines is viewed as a challenge. Identifying a representative set of streamlines that captures the flow behavior can be achieved by either strategically placing seed points or selecting a subset of precomputed streamlines that exhibit desired properties. Over the past two decades, as desired characteristics and hardware resources have evolved, the approaches to solving the challenge have greatly varied. Primarily automatic techniques, these algorithms can be classified into density-based, feature-based, and similarity-based methods. In this report, we further subdivide each category to identify the strategies adopted by various researchers. We identified a total of 18 automatic technique strategies and 2 manual technique strategies. In addition to the qualitative and quantitative comparisons established by these works, we evaluate the strategies based on criteria specifically relevant to us, i.e., redundancy, regions of interest, and computation. We believe our classification and categorization reporting benefits future research endeavors with regard to in situ flow visualization techniques where seed placement and streamline selection will be key to successful flow exploration.