As shown in Fig. Two baseline approaches are proposed based on a deep convolutional neural network GoogLeNet [ 11 ] treating the task of dating images as a classification and regression problem, respectively.
Experimental results show the feasibility of the suggested approaches which are superior to annotations of untrained humans. The remainder of the paper is organized as follows. Section 2 reviews related work on dating historical images. Section 3 introduces the Date Estimation in the Wild dataset as well as the baseline approaches in detail.
The experimental setup and results are presented in Sect. Section 5 concludes the paper. The first work that deals with dating historical images stemming from different decades has been introduced by Schindler et al. The authors present an approach to sort a collection of city-scape images temporally by reconstructing the 3D world, requiring many overlapping images of the same location. Jae et al. He et al. While He et al. Ginosar et al. More closely related to our work, Palermo et al.
They combine different color descriptors to model the historical color film processes. The results on the proposed dataset, which contains images from to , are further improved by Fernando et al.
Martin et al. However, the aforementioned approaches either rely on color photography, which was very uncommon before , or focus on specific concepts. In this section, the Date Estimation in the Wild dataset Sect. Number of crawled images and the accuracy of the provided timestamps for each year in the Date Estimation in the Wild dataset. In order to obtain reliable validation and test sets that match the dataset distribution, a maximum number of 75 unique images for to and unique images for the remaining years were extracted.
Subsequently, unique images were extracted for the validation set and another 16 per year were selected manually to obtain the test dataset containing images. The remaining images constitute the training set. Two baseline approaches are realized by training a GoogLeNet [ 11 ] and treating image date estimation as a classification or regression problem, respectively.
Upload your photos and find out where they were taken. The result would be a map view of your photo with detailed address and additional EXIF information if available. Our system utilizes EXIF data which is available in almost all photos taken with digital cameras, smartphones and tablets. Depending on the brand and model of the camera; EXIF data includes information such as; shutter speed, exposure compensation, F number, ISO speed, flash usage, date and time the image was taken, whitebalance, auxiliary lenses that were used and resolution.
Below, you can find a more detailed listing of all data Pic2Map provides. If the recording device has a built-in GPS receiver and geotagging was enabled; it is also possible to extract the coordinates where the image was taken. This data includes but not limited to the latitude, longitude, altitude and direction information. Pic2Map photo mapper will analyze all this information to pinpoint the location on map and reverse geocode the coordinates to a detailed address if possible.
Calle Real, Navia, , Spain. Klettersteig Eggishorn, Wallis, Switzerland. Frenchlaan, Ypres, West Flanders, Belgium. Bijlanderpad, Ypres, West Flanders, Belgium. Am Dorfteich, Brandenburg, Germany. EXIF is a standard that defines specific information related to an image captured by a digital camera, smartphone or a tablet.
This data is called EXIF metadata, and accessing it varies from device to device. They say a photo is worth a thousand words—a statement that certainly has some truth when you consider digital photos.
EXIF metadata is hidden technical data saved with photos taken on cameras, smartphones, and other imaging devices. When you take a photo on a camera or smartphone, information is stored as part of the image file itself, including the GPS location showing where the photo was taken if your device has the ability to record that.
It also includes the make and model of the camera, the image resolution, as well as various photographic data including exposure and shutter speed. Photo editing tools like Photoshop can immediately access this data to allow you to quickly change certain image settings, for instance.
The Exif Metadata app is free to use, with paid in-app purchases available to remove ads and allow you to edit the metadata. You can install it from the iOS App Store.
With over thousand downloads, one of the most popular apps on Android for this purpose is Photo Exif Editor. He holds an engineering degree in Computer Science I. Read more on Lifehacker and YourStory. We build bespoke solutions that use the capabilities and the features of Google Workspace for automating business processes and driving work productivity. Published in: Google Maps. Share on:. Looking for something?
Find here!
0コメント