Watch this video to see what we added to the latest version of Amped FIVE (Update 12727) that includes Timeline, Multiview, HEIC support and more!
With the new year comes a new update to Amped FIVE with some exciting new features and a couple of brand new filters!
If one of your regular tasks is producing video for presentation purposes, you’ll be excited to know that there is now the option in Amped FIVE to combine multiple video chains together in our new Timeline filter, found under the Link group of filters.
Yes, you heard correctly – we’re here with yet another update! We’ve added some highly sought-after features to Amped DVRConv, the fastest and easiest way to convert proprietary video formats.
Settings Lock Down Option
Sometimes system administrators need to lock down the settings of Amped DVRConv in order to avoid having users modify the settings accidentally, which could disrupt the workflow of the lab; for example setting a conversion to transcode instead of stream copy. Now it is possible to protect these settings, allowing only system administrators to modify them!
In our latest update to Amped FIVE, you’ll find two new filters that work together to stabilize and enhance video with an object that has some change in perspective as it moves: Perspective Stabilization and Perspective Super Resolution.
Let’s take a look at how they work!
You can also watch the two filters in action in our latest video found here:
I recently testified in court as a forensic image and video expert and, as is sometimes the case, the use of some filters to enhance images was questioned. As I have written before, there is some processing that should be entirely avoided, since it lacks accuracy and repeatability. For example, we should avoid techniques which add new information relying on data obtained by a training set, or techniques which have a random component.
Some years ago, there was a school of thought that said, only classical image processing techniques available for the analog photography can be applied to digital photography in the forensic context. What are the risks of applying the wrong processing? We are not interested in having a “pleasant” image, we are concerned about extracting information from it. The risks of wrong processing are:
- Removing existing information: for example, removing the grain in a dark image can remove also important details.
- Adding new information: for example, creating or amplifying image artifacts which may be misinterpreted as a real detail.
In this reasoning, we are not referring to details at the pixel level, but at the image semantic content. In general, if I resize an image, I add a lot of new pixels but if the processing is correct I am not adding any new relevant information.
It’s important to understand that most of the image processing techniques present a compromise: I enhance something at the expense of damaging something else. For example, if I lighten an image to show better a dark part, it’s very likely to lose details in the parts of the image that are already bright enough.
For this reason, it’s very difficult, in general, to say which techniques are good and which techniques are bad. Their applicability must be related to the specific case and the parameters used. Filters are just tools, and as such, they can be used in the right way, obtaining better images, or in the wrong way, damaging the image quality or presenting wrong information.
Because of this, it’s important not to blindly apply different enhancement and restoration filters, but to apply them in order to correct a specific defect. Similarly, the tuning of their parameters must be consistent with the amount of defect I want to correct. Abusing the filters can create images which are much worse than the original.
It is therefore important, as I’ve said many times, to work with experts who have specific experience in the forensic image and video analysis field. Who know what to do, and how to identify what has been done incorrectly.
A lot of pressure may be put on the processing done by the experts, but most people ignore that there are many other processing and possible issues happening during the image acquisition and visualization phases.
A lot of processing happens in the camera itself, from CCTV to smartphones. Unless raw image pictures are used, and this is very rare, the value of the pixels in an image are hugely dependent on the processing and encoding which automatically happens inside the device to obtain the ratio between image quality and technical limitations that the producer wished to obtain.
And then, even to simply visualize the image, there’s a lot going on under the hood. Different software can decode the image in a slightly different way which can enormously impact the final result, and a lot of image processing happens on the graphics card of the PC, on the screen, or on a projector. Just play with the brightness of the projector to realize how much the visible information in an image can be impacted by such simple tuning.
There is then the most critical part of the processing: our eyes and our brain. Different people see and want to see different things in the same image. Analyzing things in an objective and unbiased way is often very difficult unless you can measure things numerically. And in fact, avoiding and limiting the various types of biases are one of the most important aspects of forensic science currently studied.
This article, written by Martino Jerian, was originally published in Lawyer Monthly magazine. Click here for the published article.
Not long has passed since the release of Amped Authenticate 10641 but… yes, the next one is already out! Amped Authenticate 11362 is now released with a lot of improvements, including two new filters based on JPEG Dimples, one of the last discoveries of the image forensics scientific community!
Despite many attempts to send JPEG into retirement, today the vast majority of digital images still use it. Amped Authenticate users know that traces left by JPEG compression are a superb asset when it comes to investigating the digital history of an image, as witnessed by the vast JPEG-based toolkit that Authenticate provides: quantization table analysis, JPEG ghosts, inconsistencies in blocking artifacts, double quantization traces in the DCT coefficients, and more.
But JPEG is still full of new surprises nowadays! A few months ago, while Amped was attending (and sponsoring!) the IEEE 2017 International Workshop on Information Forensics and Security (WIFS 2017), a new footprint was presented to the scientific community: JPEG Dimples (click here to see the original work Photo forensics from JPEG dimples by Shruti Agarwal and Prof. Hany Farid).
JPEG Dimples manifest themselves as a grid of slightly brighter/darker pixels, spaced by 8 pixels in each dimension. Like most image forensic fingerprints, even JPEG Dimples are hardly visible by the human eye, but they can be easily detected with a proper algorithm.
But why does this grid appear? And why is it important for our analysis? We’ll answer these questions in detail in a future blog post, however the reason behind JPEG Dimples is rather simple: during the DCT coefficients quantization phase, different operators exist to approximate decimal values to integer values: the round operator (which approximates the decimal number to the nearest integer) the floor operator (approximation to the nearest smaller integer) or the ceil operator (approximation to the nearest bigger integer). The table below shows the difference in approximating a Value (first column) to an integer using round, floor and ceil.
Obviously, using floor tends to produce smaller values in the 8-by-8 DCT block than using round, and the opposite with ceil. And when we go back to the pixel domain, this leads to a slightly darker or brighter pixel on the top-left corner of the pixel block (see example below)! Measuring the presence of this grid will tell us to which degree an image contains the JPEG Dimples footprint.
Now you may be wondering “well, how many cameras will ever be using floor or ceil in place of the more classical round?” Not so few, actually. According to the work presented at WIFS 2017, more than 60% of tested cameras do introduce Dimples. We also carried out an internal evaluation on Amped datasets and numbers were less upsetting, still, we found Dimples in roughly 30% of tested cameras. A footprint with such a spread could not be missing in Amped Authenticate, and so here we are. Continue reading
If you’ve attended one of my classes or lectures, you’ve likely heard me say the following phrase many times, “There’s what you know, and there’s what you can prove.” The essence of this statement forms the basis of the Criminal Justice system as well as science.
What I “know” is subject to bias. What I “know” is found in the realm of truth. As a Kansas City Chiefs supporter, I “know” that the Oakland Raiders are a horrible team. I “know” that their fans are the worst in the world. After all, the Chiefs are the best and their fans are as pure as the wind-driven snow. This is “true” to me. Whilst funny and used to illustrate a point (I’m sure there are some really great people among the Raiders fan base), truths are things we “know.” Truths are rooted deep in feelings/emotions and unlikely to be changed by facts. There is a segment of the US population that believes it true that Elvis is still alive and that he’s likely hanging out on some Caribbean island with Tupac and Biggy Smalls.
Facts are measurable; they form the basis of tests of reliability. I can measure the temperature in a specific location and you, standing in the same location, can perform the same test and come to the same measurement. Supported by facts, our tests in this discipline become reliable, repeatable, and reproducible. Our conclusions can thus be trusted.
What on earth does this all have to do with Amped FIVE and Forensic Multimedia Analysis? I’m glad you asked.
By now, you’re well familiar with the fact that Amped Software operationalizes tools out of image science, math, statistics, etc. We also operationalize tools and training out of the world of psychology. By this I mean if we’re going to work in the visual world, we must know how that visual world operates not only from a mechanical standpoint but also from how the brain processes the inputs from its collection devices.
Whilst it’s been a busy time for us here at Amped with the demand for training higher than ever, we have made sure our development is continuous and we’re here again with another huge update for Amped FIVE.
A Completely Revamped Conversion Engine
As you will know, one of the biggest struggles within the world of CCTV and video analysis is the ever-increasing number of proprietary formats. Our support and development team are constantly receiving requests for new format support and in our latest update, we have enabled conversion support for BVR, DVS, H64, PSF and SHV formats, along with some variations of other formats already supported in previous versions.
All these formats are multiplexed streams. This is when a manufacturer has placed all camera footage into a single time-based video stream.
The latest FIVE not only converts the files straight away, but demultiplexes each video stream, splitting them into their own individual chains within the software. Under the Convert DVR Advanced tab you will find the options to enable this time-saving function.
Files to Convert > All, one chain per file.
No more mixed streams, no more time wasted writing carving scripts. A few clicks will now save you hours!
Multiplexed single stream decoding is huge, so expect a dedicated blog post in the next few weeks looking more deeply into decoding files of this type.
But the new conversion engine does not stop there! There are a lot of benefits even on single stream video files. Standard conversion done with vanilla FFmpeg is often not enough – there may be the risk of losing video frames because of wrongly interpreted proprietary metadata. Our new engine not only cleans almost every proprietary video format, being in MPEG4, H263, H264 and H265, but for many of them also recovers the proprietary timestamp. We found more than 50 different variations of timestamp formats!
First of all, let me introduce myself. I’m Lucy Carey-Shields, the newest member of the Amped team! Originally from the UK I studied Computer Forensics at degree level and was a volunteer police officer with a UK police force for six years. I later went on to work for another UK police force for almost four years as a digital forensics technician, mostly working with CCTV and video whilst also providing forensic acquisition of mobile devices. Whilst working at Amped I’ll be providing support as well as putting the software through its paces, so I look forward to hearing from you all! Now let’s dive into my first Amped blog post!
When dealing with video, we often have to hide sensitive information or protect a person’s identity, particularly if the video is to be shared with a wider audience and we need to control the display of certain information. Amped FIVE has a filter for that!
Having used two or more different tools to load, process and then redact sensitive footage in the past, I know how time-saving having all these features in one piece of software can be (and how critical time can be in a law enforcement environment).
The Hide Selection filter allows you to pixelate, blur or blacken anything you want masked in a video quickly. In this instance, we’ll explore both dynamic tracking and manual tracking during the use of Hide Selection. Hide Selection can be found under the Presentation group of filters, typically used at the end of a workflow.
Redaction, whilst usually done towards the end of processing a video, is arguably one of the more critical steps in a workflow as revealing sensitive data or someone’s identity could have serious and potentially dangerous consequences. With this in mind, it’s important we ensure frame by frame accuracy so that the subjects we want to censor are completely disguised. FIVE allows you to apply the filter by selecting the necessary points – maintaining that important frame by frame accuracy. Continue reading
The ability to save a frame as a “Snapshot” has been a feature in Amped FIVE for quite some time. A simplified explanation of the use of Snapshots in interacting with third-party programs can be found here.
Today, I want to expand a bit on the use of Snapshots in your processing of video files.
There are often times that users have been asked to produce a BOLO flyer of multiple subjects and problems with the video file complicate the fulfillment of the request.
- The subjects aren’t looking towards the camera at the same time / within the same frame.
- There’s only one good frame of video to work with and you need to crop out multiple subjects.
Enter the Snapshot tool.
The Snapshot tool, on the Player Panel, saves the snapshot of the currently displayed image (frame) and its relative project.
When you Right Click on the button, a menu pops up.
The post linked above talks about working with the listed third-party tools. In this case, we’ll save the frame out, selecting a file type and manually enter an appropriate file name.
We can choose from a variety of file types. In most cases, analysts will choose a lossless format like TIFF.
The results, saved to the working folder, are the frame of video as a TIFF and its relative project file (.afp).
Working in this way, analysts can quickly and easily work with frames of interest separate from the video file. The same frame can be added to the project several times, repeated as necessary (in the case of cropping multiple subjects and objects from the same frame).
Amped FIVE is an amazingly flexible tool. The Snapshot tool, found in the Player Panel, provides yet another way to move frames of interest out of your project as files, or out to a third-party tool.
If you’d like more information about our tools and training options, contact us today.