Spectre – Does it work?

Over a year ago I installed Spectre (for IOS). The thought of having a piece of software that could remove moving objects from photographs seemed like a real cool idea. It is essentially a long-exposure app which uses multiple images to create two forms of effects: (i) an image sans moving objects, and (ii) images with light (or movement) trails. It is touted as using AI and computational photography to produce these long exposures. The machine learning algorithms provide the scene recognition, exposure compensation, and “AI stabilization”, supposedly allowing for up to a 9-second handheld exposure without the need for a tripod.

It seems as though the effects are provided by means of a computational photography technique known as “image stacking“. Image stacking just involves taking multiple images, and post-processing the series to produce a single image. For removing objects, the images are averaged. The static features will be retained in the image, the moving features will be removed through the image averaging process – which is why a stable image is important. For the light trails it works similar to a long exposure on a digital camera, where moving objects in the image become blurred, which is usually achieved by superimposing the moving features from each frame on the starting frame.

Fig.1: The Spectre main screen.

The app is very easy to use. Below the viewing window are a series of basic controls: camera flip; camera stabilization, and settings. The stabilization control, when activated, provides a small visual feature that determines when the iPhone is STABLE. As Spectre can perform a maximum of 9 seconds worth of processing, stabilization is an important attribute. The length of exposure is controlled by a dial in the lower-right corner of the app – you can choose between 3, 5, and 9 seconds. The Settings really only allows the “images” to be saved as Live Photos. The button at the top-middle turns light trails to ON, OFF, or AUTO. The button in the top-right allows for exposure compensation, which can be adjusted using a slider. The viewing window can also be tapped to set the focus point for the shot.

Fig.2: The use of Spectre to create a motion trail (9 sec). The length of the train, and the slow speed it was moving at created slow-motion perception.

Using this app allows one of two types of processing. As mentioned, one of these modes is the creation of trails – during the day these are motion trails, and at night these are light trails. Motion trails are added by turning “light trails” to the “ON” position (Fig.4). The second mode, with “light trails” to the “OFF” position, basically removes moving objects from the scene (Fig.3)

Fig.3: Light trails off with moving objects removed.
Fig.4: Light trails on with motion trails shown during daylight.

It is a very simple app, for which I do congratulate the app designers. Too many photo-type app designers try and cram 1001 features into an app, often overwhelming the user.

Here are some caveats/suggestions:

  • Sometimes motion trails occur because the moving object is too long to fundamentally change the content of the image stack. A good example is a slow moving train – the train never leaves the scene, during a 9-second exposure, and hence gets averaged into a motion trail. This is an example of a long-exposure image, as aptly shown in Figure 2. It’s still cool from as aesthetics point-of-view.
  • Objects must move in and out of frame during the exposure time. So it’s not great for trying to remove people from tourist spots, because there may be too many of them, and they may not move quick enough.
  • Long exposures tend to suffer from camera shake. Although Spectre offers an indication of stability, it is best to rest the camera on at least one stable surface, otherwise there is a risk of subtle motion artifacts being introduced.
  • Objects moving too slowly might be blurred, and still leave some residual movement in a scene where moving objects are to be removed.

Does this app work? The answer is both yes and no. During the day the ideal situation for his app is a crowded scene, but the objects/people have to be moving at a good rate. Getting rid of parked cars, and slow people is not going to happen. Views from above are obviously ideal, or scenes where the objects to be removed are moving. For example, doing light trails of moving cars at night produces cool images, but only if they are taken from a vantage point – photos taken at the same level of the cars only results in producing a band of bright light.

It would actually be cool if they could extend this app to allow for times above nine seconds, specifically for removing people from crowded scenes. Or perhaps allowing the user to specify a frame count and delay. For example, 30 frames with a 3 second delay between each frame. It’s a fun app to play around with, and well worth the $2.99 (although how long it will be maintained is another question, the last update was 11 months ago).

A review of SKRWT – keystone correction for IOS

For a few years now, I have been using  SKRWT, an app that does perspective correction in IOS.

The goal was to have some way of quickly fixing issues with perspective, and distortions, in photographs. The most common form of this is the keystone effect (see previous post) which occurs when the image plane is not parallel to the lines that are required to be parallel in the photograph. This usually occurs when taking photographs of buildings where we tilt the camera backwards, in order to include the whole scene. The building appears to be “falling away” from the camera. Fig.1 shows a photograph of a church in Montreal. Notice, the skew as the building seems to tilt backwards.

The process of correcting distortions with SKRWT is easy. Pick an image, and then a series of options are provided in the icon bar below the imported picture. The option that best approximates the types of perspective distortion is selected, and a new window opens, with a grid overlaid upon the image. A slider below the image can be used to select the magnitude of the distortion correction, with the image transformed as the slider is moved. When the image looks geometrically corrected, pressing the tick stores the newly corrected image.

Using the SKRWT app, the perspective distortion can be fixed, but at a price. The problem is that correcting for the perspective distortion requires distorting the image, which means it will likely be larger than the original, and will need to be cropped (otherwise the image will contain black background regions).

Here is a third example, of Toronto’s flatiron building, with the building surrounded by enough “picture” to allow for corrective changes that don’t cut off any of the main object.

Overall the app is well designed and easy to use. In fact it will remove quite complex distortions, although there is some loss of content in the images processed. To use this, or any similar perspective correction software properly, you  really have to frame the building with enough background to allow for corrections – not so you are left with half a building.

The sad thing about this app is something that plagues a lot of apps – it has become a zombie app. The developer was suppose to release version 1.5 in December 2020, but alas nothing has appeared, and the website has had no updates. Zombie apps work while the system they are on works, but upgrade the phone, or OS, and there is every likelihood it will no longer work.