I need to develop a mobile app (primarily for Android, iOS, and Windows Mobile) for face detection. Obviously, OpenCV is the most well known. However, I'm unsure about the compatibility among the different OS'es. Besies OpenCV, are there other options? 2 key requirements:
-Open source/commercial libraries but must run locally/natively in devices without internet connection so Player Service API would not work
-Capable of tracking multiple faces in motion
Anyone can share their experiences/knowledge in this area? Any pointers greatly appreciated!
You are really pushing the margin a whole lot.
Face detection generally consists of three different areas.
1) Recognizing a face as a face (there is a mouth, a nose, eyes) This is useful for focusing a snapshot.
2) Recognizing facial features, looking for emotion (mouth in a smile) or eye tracking.
3) Facial recognition. Using the system to perform identification by attaching a name to a face.
You want to use a face recognition tool to perform tracking and count people entering a particular place, using a mobile phone.
First tracking is pretty difficult. Its one thing to perform simple face identity in a single frame snap shot. That's pretty easy. The problem is, you may find your frame rates so poor that you can only accommodate 1 frame every three or even every five seconds. That will make it nearly impossible to track and count faces. Counting faces is easy, but what's hard is to determine if that face in the screen was counted previously or is a new person entering the screen.
OpenCV has a whole lot of tools and examples out there for facial recognition, image tracking, etc. I'd strongly recommend playing with OpenCV and test its capabilities. I'd recommend the C/C++ versions (unless you are already a Python programmer) Here's a place to start, a blog entry I wrote a few months ago.
I really like the tutorials from Kyle Hounslow... Look him up on youtube. His videos are well thought out, they are interesting and he provides example code for all his work. Go ahead and watch all of those videos, and repeat all of those examples. Get a feel for what is available in frame rates using a laptop.
The next part of your task is porting stuff from OpenCV to Android/iOS. That's no easy task. I'm sure folks have tried, and I'm sure helpful hints are out there.
I don't mean to dissuade you from an awesome investigation but do note what you want to do is mighty difficult. You will have to invest some time to even determine where all the difficult areas are. And unfortunately you won't know effective frame rates and performance until you build some stuff and try it.
Good luck with the journey.
Related
We are having a Skill built for us which plays podcasts and audio snippets of videos. We currently serve all of this content through other traditional platforms like native mobile apps and a website.
One problem we have is that the volume of all this audio content is much lower than the rest of the sounds outputted from the Alexa device. We don't notice any similar discrepancies on the other aforementioned platforms, and the developers building the Skill say that there's no API which allows you to boost or manipulate the output volume (not the system volume).
Has anyone else had experiences with this sort of issue? We are reluctant to pump up the volume of our source files as it will affect all the other places they are listened to.
Short answer - yes it's tricky and you're not alone.
As detailed in this BBC report* on designing a voice application - "All of our experts have experienced problems in audio levels when mixing and mastering audio for smart speakers."
Official guidence from Amazon is:
Program loudness for Alexa should average -14 dB LUFS/LKFS
The true-peak value should not exceed -2 dBFS
It then goes so far as to say that,
Your skill may be rejected if program loudness:
Is lower than -19 dB LUFS
Is higher than -9dB LUFS
However, this mainly seems to apply to audio played either as part of a Flash Briefing or using the AudioPlayer Interface, and you may get away with deviating from this if using it as part of SSML output.
That said, in practice developers tend to bump the levels up on audio until it sounds good. Sticking strictly to the recommendations usually renders the volume way too low.
So, if you didn't want to increase the loudness of clips as it'd affect other platforms, your best options might be to create an Alexa-version of the audio - mixed slightly louder. Though, I recognize that this would be tedious.
*In the interest of transparency, I wanted to declare that I fed into this report.
I want to build a free app to become familiar with what is required, but I was always confused about the steps one needs to take to START a software project.
What are the steps required in order to develop a mobile app?
I will list some of the things I think should be done but I don't necessarily know how to do. Any advice, details and technologies you have to accomplish these steps would be awesome.
Decide which platform you want to develop. What are some of the pros and cons in this area for android vs iOS vs Windows8?
How to test the app - can you get free hardware to test with a well detailed app plan? Emulator?
Detail what you want the app to do and which functionalities you want.
Research if this app already exists. What are some areas of concerns in terms of not breaking the law such as patent infringement etc?
Setup a source repository such as git (google a guide I guess?)
Look at guides to familiarize yourself with APIs and write sample code to learn what you need?
Start the development and keep doing the above as needed.
Starting a software project can be as easy as start writing code. Most programmers will have an intuition as to what needs to be done and how it could be done. The other extreme of starting a software project is to start with talking to a client (or looking at the world) and figuring out what the problem is. I find that a thorough understanding of the problem you are trying to address with a project is already a long way into getting the project done painlessly. It'll give you a good understanding of what is required for you to call your project done.
So I guess point number one becomes: know what the problem is you're solving. Knowing this will also tell you if any existing app solves the same problem to a satisfying standard.
NOTE: I am not that familiar with the Windows 8 platform so my answer mostly talks about iOS and Android. The issues raised however are broad enough to cover large parts of the Windows platform.
Platform
Selecting a deployment platform is an important part of a launching a product, and a lot of other decisions depend on the platform. We are in the unfortunate state that two major mobile OSes exist that are separate in terms of code development and reuse. When considering selecting your deployment platform you'll want to think about the audience, and the (potential) sub set of the audience that is willing to pay for your application. Android might have to most devices out there but iPhone makes the most money (also for developers). However, remember that there are lots of apps out there and most developers don't ever make any (or not enough) money out of their apps.
Getting into app development with the aim of getting rich is going to leave you dissappointed. That's not very likely, then again someone always wins the lottery as well. It is a good way though to get employed and make some money that way.
Then there is the question of programming language (Java, Objective-C or C#). This is largely decided on what you are already familiar with, and if you aren't then refer back to the previous point.
Testing
Testing the product is a tricky thing. You'll have to start off with the emulator (which is usually provided with the development pack). Sooner or later however you'll have to test the app on hardware. I doubt you'll get your hands on free hardware but borrowing from friends and relatives is always an option. There may also be businesses that rent out test hardware to developers, if there isn't then I suppose that's one business idea to work on.
The platform choice will affect this also. Android is running on a much wider range of hardware than iOS.
Patent infringment
I don't know that much about patent issues, other than software patents are nasty. As a single developer I wouldn't be too worried about infringing on patents, the main purpose of them is to keep competitors at bay. What usually ends up happening is that big companies kill off competition with patent lawsuits, or they buy a smaller company that holds a nice collection of patents.
If you want to be on the safe side (meaning you own a company and are really doing this to make money) then talk to patent lawyers.
Code repository
A code hosting service like GitHub is fantastic in that it not only provides a place to have you code, but it also provides issue trackers for keeping notes on the functionality that is still missing or bugs that have crept up in your software.
The best places to start learning about Git are git-scm.com and the GitHub help pages.
Software development plan
Your last point explodes to a thing called software engineering. There has been lots of research into different ways of managing software development projects. The idea being that software development tends to be extended over long periods of time, the requirements of the project change during the project (as you learn more) and the project can involve anything from 1 to 100s of developers. Some way coordinating work between those developers (and all other parties involved like customers) has to be formalised, enter software engineering. The aim is to define a methodology and project structure that guides the development process and makes it more likely that the requirements are met at the end of the project.
Some models worth looking into include (Test Driven Development and other agile methods).
Finally I would add to the list of things that need to be done
Research libraries, note that this comes before familiarising yourself with the APIs of those libraries.
What software already exists that does a part of what you want to achieve. This goes partly back to the question of what platform to use. Apple has put a lot of attention in developing easy to use frameworks to support iOS app development. I am not that familiar with Andoird's or Windows 8 but the less code you have to write the faster the product will be done.
1 http://mobiledevices.about.com/od/kindattentiondevelopers/tp/Android-Os-Vs-Apple-Ios-Which-Is-Better-For-Developers.htm
There is only one step needed: Just start that project!
You are going to develop a free application, so it should be fun to do that. Choose whatever you like and keep going:
Make sure you are productive enough -- 10 Laws of Productivity
Avoid complexity -- Occam's razor, KISS principle
Let CI system do the boring stuff -- Machines should work; people should think.
Read books and improve yourself.
Please also avoid blind decisions. If you simply try several available options you'll eventually find the best way to achieve your goals. Do some PoC and decide. Nowadays 1-2 hours should be enough to start with any technology. This is the rule of maturity. You have your own goals, so it is better to avoid immature solutions.
Happy coding.
CPlayer I came to this forum with the same question since I am new to mobile app design and want to make my own app. I realize it is important to take certain steps in the correct order so that wasted time is minimized or eliminated. I did some research and came across two online sources I believe, if they are put together as one, will make one better source. The links are:
http://answers.oreilly.com/topic/2311-a-mobile-app-development-checklist/
http://mobiledevices.about.com/od/kindattentiondevelopers/ht/How-To-Create-An-App-For-The-Iphone.htm
Good Luck,
laroice
I need help to chose a project to work on for my master graduation, The project must involve Ai / Machine learning or Business intelegence.. but if there is any other suggestion out of these topics it is Ok, please help me.
One of the most rapid growing areas in AI today is Computer Vision. There are many practical needs where the results of your Master Thesis can be helpful. You can try research something like Emotion Detection, Eye-Tracking, etc.
An appropriate work for a MS in CS in any good University can highlight the current status of research on this field, compare different approaches and algorithms. As a practical part, it makes also a lot of fun when your program recognizes your mood properly :)
Netflix
If you want to work more on non trivial datasets (not google size, but not trivial either and with real application), with an objective measure of success, why not working on the netflix challenge (the first one) ? You can get all the data for free, you have many papers on it, as well as pretty good way to compare your results vs other peoples (since everyone used exactly the same dataset, and it was not so easy to "cheat", contrary to what happens quite often in the academic literature). While not trivial in size, you can work on it with only one computer (assuming it is recent enough), and depending on the type of algorithms you are using, you can implement them in a language which is not C/C++, at least for prototyping (for example, I could get decent results doing things entirely in python).
Bonus point, it passes the "family" test: easy to tell your parents what you are working on, which is always a pain in my experience :)
Music-related tasks
A bit more original: something that is both cool, not trivial but not too complicated in data handling is anything around music, like music genre recognition (classical / electronic / jazz / etc...). You would need to know about signal processing as well, though - I would not advise it if you cannot get easy access to professors who know about the topic.
I can use the same answer I used on a previous, similar question:
Russ Greiner has a great list of project topics for his machine learning course, so that's a great place to start.
Both GAs and ANNs are learners/classifiers. So I ask you the question, what is an interesting "thing" to learn? Maybe it's:
Detecting cancer
Predicting the outcome between two sports teams
Filtering spam
Detecting faces
Reading text (OCR)
Playing a game
The sky is the limit, really!
Since it has a business tie in - given some input set determine probable business fraud from the input (something the SEC seems challenged in doing). We now have several examples (Madoff and others). Or a system to estimate investment risk (there are lots of such systems apparently but were any accurate in the case of Lehman for example).
A starting point might be the Chen book Genetic Algorithms and Genetic Programming in Computational Finance.
Here's an AAAI writeup of an award to the National Association of Securities Dealers for a system thatmonitors NASDAQ insider trading.
Many great answers posted already, but I wanted to add my 2 cents.There is one hot topic in which big companies all around are investing lots of resources into, and is still a very challenging topic with lots of potential: Automated detection of fake news.
This is even more relevant nowadays where most of us are connecting though social media and there's a huge crisis looming over.
Fake news, content removal, source reliability... The problem is huge and very exciting. It is as I said challenging as it can be seen from many perspectives (from analising images to detect fakes using adversarial netwotks to detecting fake written news based on text content (NLP) or using graph theory to find sources) and the possbilities for a research proyect are endless.
I suggest you read some general articles (e.g this or this) or have a look at research articles from the last couple of years (a quick google seach will throw you a lot of related stuff).
I wish I had the opportunity of starting over a project based on this topic. I think it's going to be of the upmost relevance in the next few years.
Screen scraping seems like a useful tool - you can go onto someone else's site and steal their data - how wonderful!
But I'm having a hard time with how useful this could be.
Most application data is pretty specific to that application even on the web. For example, let's say I scrape all of the questions and answers off of StackOverflow or all of the results off of Google (assuming this were possible) - I'm left with data that is not very useful unless I either have a competing question and answer site (in which case the stolen data will be immediately obvious) or a competing search engine (in which case, unless I have an algorithm of my own, my data is going to be stale pretty quickly).
So my question is, under what circumstances could the data from one app be useful to some external app? I'm looking for a practical example to illustrate the point.
It's useful when a site publicly provides data that is (still) not available as an XML service. I had a client who used scraping to pull flight tracking data into one of his company's intranet applications.
The technique is also used for research. I had a client who wanted to compare the contents of several online dictionaries by part of speech, and all of these sites had to be scraped.
It is not a technique for "stealing" data. All ordinary usage restrictions apply. Many sites implement CAPTCHA mechanisms to prevent scraping, and it is inappropriate to work around these.
A good example is StackOverflow - no need to scrape data as they've released it under a CC license. Already the community is crunching statistics and creating interesting graphs.
There's a whole bunch of popular mashup examples on ProgrammableWeb. You can even meet up with fellow mashupers (O_o) at events like BarCamps and Hack Days (take a sleeping bag). Have a look at the wealth of information available from Yahoo APIs (particularly Pipes) and see what developers are doing with it.
Don't steal and republish, build something even better with the data - new ways of understanding, searching or exploring it. Always cite your data sources and thank those who helped you. Use it to learn a new language or understand data or help promote the semantic web. Remember it's for fun not profit!
Hope that helps :)
If the site has data that would benefit from being accessible through an API (and it would be free and legal to do so), but they just haven't implemented one yet, screen scraping is a way of essentially creating that functionality for yourself.
Practical example -- screen scraping would allow you to create some sort of mashup that combines information from the entire SO family of sites, since there's currently no API.
Well, to collect data from a mainframe. That's one reason why some people use screen scraping. Mainframes are still in use in the financial world and often it's running software that has been written in the previous century. The people who wrote it might already be retired and since this software is very critical for these organizations, they really hate it when some new code needs to be added. So, screenscraping offers an easy interface to communicate with the mainframe to collect information from the mainframe and then send it onwards to any process that needs this information.
Rewrite the mainframe application, you say? Well, software on mainframes can be very old. I've seen software on mainframes that was over 30 years old, written in COBOL. Often, those applications work just fine and companies don't want to risk rewriting parts because it might break some code that had been working for over 30 years! Don't fix things if they're not broken, please. Of course, additional code could be written but it takes a long time for mainframe code to be used in a production environment. And experienced mainframe developers are hard to find.
I myself had to use screen scraping too in a software project. This was a scheduling application which had to capture the output to the console of every child process it started. It's the simplest form of screen scraping, actually, and many people don't even realize that if you redirect the output of one application to the input of another, that it's still a kind of screen scraping. :)
Basically, screen scraping allows you to connect one (web) application with another one. It's often a quick solution, used when other solutions would cost too much time. Everyone hates it, but the amount of time it saves still makes it very efficient.
Let's say you wanted to get scores from a popular sports site that did not offer the information available with an XML feed or API.
For one project we found a (cheap) commercial vendor that offered translation services for a specific file format. The vendor didn't offer an API (it was, after all, a cheap vendor) and instead had a web form to upload and download from.
With hundreds of files a day the only way to do this was to use WWW::Mechanize in Perl, screen scrape the way through the login and upload boxes, submit the file, and save the returned file. It's ugly and definitely fragile (if the vendor changes the site in the least it could break the app) but it works. It's been working now for over a year.
One example from my experience.
I needed a list of major cities throughout the world with their latitude and longitude for an iPhone app I was building. The app would use that data along with the geolocation feature on the iPhone to show which major city each user of the app was closest to (so as not to show exact location), and plot them on a 3D globe of the earth.
I couldn't find an appropriate list in XML/Excel/CSV type format anywhere easily, but I did find this wikipedia page with (roughly) the info I needed. So I wrote up a quick script to scrape that page and load the data into a database.
Any time you need a computer to read the data on a website. Screen scraping is useful in exactly the same instances that any website API is useful. Some websites, however, don't have the resources to create an API themselves; screen scraping is the developer's way around that.
For instance, in the earlier days of Stack Overflow, someone built a tool to track changes to your reputation over time, before Stack Overflow itself provided that feature. The only way to do that, since Stack Overflow has no API, was to screen scrape.
The obvious case is when a webservice doesn't offer reverse search. You can implement that reverse search over the same data set, but it requires scraping the entire dataset.
This may be fair use if the reverse search also requires significant pre-processing, e.g. because you need to support partial matching. The data source may not have the technical skills or computing resources to provide the reverse search option.
I use screen scraping daily, I run some eCommerce sites and have screen-scraping scripts running daily to gather product lists automatically from my suppliers wholesale sites. This allows me to have upto date information on all the products available to me from several suppliers and allows me to flag non-economical margins due to price changes.
When desinging UI for mobile apps in general which resolution could be considered safe as a general rule of thumb. My interest lies specifically in web based apps. The iPhone has a pretty high resolution for a hand held, and the Nokia E Series seem to oriented differently. Is 240×320 still considered safe?
Not enough information...
You say you're targeting a "Mobile App" but the reality is that mobile could mean anything from a cell phone with 128x128 resolution to a MID with 800x600 resolution.
There is no "safe" resolution for such a wide range, and if you're truly targeting all of them you need to design a custom interface for each major resolution. Add some scaling factors in and you might be able to cut it down to 5-8 different interface designs.
Further, the UI means "User Interface" and includes a lot more than just the resolution - you can't count on a touchscreen, full keyboard, or even software keys.
You need to either better define your target, or explain your target here so we can better help you.
Keep in mind that there are millions of phone users that don't have PDA resolutions, and you can really only count on 128x128 or better to cover the majority of technically inclined cell phone users (those that know there's a web browser in their phone, nevermind those that use it).
But if you're prepared to accept these losses, go ahead and hit for 320x240 and 240x320. That will give you most current PDA phones and up (older blackberries and palm devices had smaller square orientations). Plan on spending time later supporting lower resolution devices and above all...
Do not tie your app to a particular resolution.
Make sure your app is flexible enough that you can deploy new UI's without changing internal application logic - in other words separate the presentation from the core logic. You will find this very useful later - the mobile world changes daily. Once you gauge how your app is being used you can, for instance, easily deploy an iPhone specific version that is pixel perfect (and prettier than an upscaled 320x240) in order to engage more users. Being able to do this in a few hours (because you don't have to change the internals) is going to put you miles ahead of the competition if someone else makes a swipe at your market.
-Adam
Right now I believe it would make sense for me to target about 2 resolutions and latter learn my customers best needs through feedback?
It's a chicken and egg problem.
Ideally before you develop the product you already know what your customers use/need.
Often not even the customers know what they need until they use something (and more often than not you find out what they don't need rather than what they need).
So in this case, yes, spend a little bit of time developing a prototype app that you can send out there to a few people and get feedback. They will have better feedback because they can try it out, and you will have a springboard to start from. The ability to quickly release UI updates without changing core logic will allow you test several interfaces quickly without a huge time investment.
Further, to customers you will seem really responsive to their needs, which will be a big benefit to people who's jobs depend on reaction time.
-Adam
You mentioned Web based apps. Any particular framework you have in mind?
In many cases, WALL seems to help to large extent.
Here's one Article, Adapting to User Devices Using Mobile Web Technology exploiting WALL.