With NeRF, we can accurately recreate the full context of a place including its lighting, the texture of materials and what’s in the background. To create these true-to-life scenes, we use neural radiance fields (NeRF), an advanced AI technique, transforms ordinary pictures into 3D representations. If you’re hungry, glide down to the street level to explore nearby restaurants - and even take a look inside to quickly understand the vibe of a spot before you book your reservation. You can also spot where it tends to be most crowded so you can have all the information you need to decide where and when to go. With the time slider, you can see what the area looks like at different times of day and what the weather will be like. ![]() You can virtually soar over the building and see where things like the entrances are. Say you’re planning a visit to the Rijksmuseum in Amsterdam. And it layers helpful information on top like the weather, traffic, and how busy a place is. Using advances in AI and computer vision, immersive view fuses billions of Street View and aerial images to create a rich, digital model of the world. Immersive view is an entirely new way to explore a place - letting you feel like you’re right there, even before you visit. Today we’re demonstrating how AI is bringing this vision to life, with updates for immersive view and Live View, along with new features for electric vehicle (EV) drivers and people who walk, bike or ride public transit. Save my name, email, and website in this browser for the next time I comment.Last year, we shared our vision for the future of Google Maps - an immersive, intuitive map that reimagines how you explore and navigate, while helping you make more sustainable choices. But due to the number of rides completed close to home his largest tile visits of almost 5000 result in a tower of over 10,000 km in height: The expanses of Dutch water make max squares particularly tricky so Koos has concentrated on expanding his max cluster from the northern tip of The Netherlands mainland right down to Liechtenstein’s capital of Vadus:īrian Toone has regularly topped the Strava distance charts and currently has over 1/4 million miles logged. The max cluster top position is currently held by Koos Woestenburg. Two clear masses of activity are accompanied by veins of exploration up to and around Scotland: In 2018 Jonathan France showed what can be done when he completed a 100×100 max square in a single year. Although the 300km towering line from Milan to San Remo, home of his 2017 victory, also stands out pretty clearly: Multiple Tour de France routes are dramatically overshadowed by training rides at his home in the South of France, Mallorca, Calpe and Canary Islands in the distance. A few examples… The WorldTour ProfessionalĪ big thanks to Michał Kwiatowski for letting me share images of his data (it isn’t public in VeloViewer): Uncheck the box to get an KML export with towers represented 1 to 1 as sown in this post.Īn interesting exercise is visiting the Activities pages of people in the main VeloViewer leaderboards who have their VeloViewer data set to public and downloading/viewing their 3D KML files. I tried logarithms first but they squashed the tall towers far too much. By default the KML file will flatten the towers by square-rooting the visit count which seems to result in a better view of the data. each tile visit results in the addition of a full height tile cube being stacked each time) as shown on the examples on this page. Typically people have a really high concentration of visits to tiles in the immediate vicinity to where they live resulting in huge towers if the 3D KML file is viewed 1 to 1 (i.e. UPDATE: New “Flatten spikes” option added. ![]() Then open up Google Earth Pro (the desktop version is best, and free, but also works in the mobile or web version) and open the KML file. Press that button and you’ll get a (possibly quite large) KML file. Make sure the Map is turned on along with either Max Square or Max Cluster and then click the map settings button: It uses a new export button found on your Activities page. I’ve wanted to produce this view of VeloViewer Explorer Tiles since I first came up with the idea back in 2015 and can only put my lack of action down to being too busy with the professional teams these last few years! Simple idea though: provide a KML output that can be viewed in Google Earth shows a tower for each ticked Explorer Tile with the height representing the number of times the tile has been visited on your travels.
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