Edge-assisted Visual Simultaneous Localization and Mapping (V-SLAM) systems offload complex analysis modules from computationally constrained mobile devices to cloud servers at the network edge. As visual data must travel through networks to reach the edge cloud, it is crucial to minimize transferred data while maintaining reliable and accurate localization and map generation. State-of-the-art systems perform pre-analysis of SLAM modules on the mobile device, causing high processing delays and limiting functionality. To minimise both throughput demand and latency, we are investigating video compression techniques in Compress-Then-Analyze (CTA) transmission systems. Evaluations employing the widely used H.264 video compression standard demonstrate that CTA achieves lower throughputs than its counterparts, as well as significantly reduced processing delays and transmission latencies. The results open up new possibilities to explore this research direction on edge-assisted V-SLAM further.