Develop Reference

Android API face detection vs. OpenCV/JavaCV face detection

I've used local Android face detection on an Android device, but it seems quite slow and I'm not so sure on the reliability. I've also used OpenCV's face detection but only on PC, as opposed to an Android device. For Android, I'm guessing I'll have to use JavaCV (or OpenCV4Android?).
Do you know what the speed differences are between Android API's facial detection and OpenCV's facial detection? I'm sure OpenCV/JavaCV is both more efficient/faster and more accurate, but cannot confirm.
Thanks!

Suggestion: If you are looking for face detection, I suggest you use platform specific APIs like FaceDetector rather than OpenCV Java wrapper. This is since those API's would be hardware accelerated(GPU) unlike OpenCV face detection which till version 3.0 relied on CPU only.
The speed difference you perceive between desktop and mobile device should be for the difference in device hardware ( like CPU ) and not because of different libraries wrappers like JavaCV/OpenCV4Android. OpenCV is written is in C/C++. All processing intensive code is still in C/C++ and the Java libraries are just wrappers over JNI.
OpenCV4Android - OpenCV.org maintained Android Java wrapper. Recommended.
OpenCV Java - OpenCV.org maintained auto generated desktop Java wrapper.
JavaCV - Popular Java wrapper maintained by independent developer(s). Not Android specific. This library might get out of sync with OpenCV newer versions.

Is RenderScript the only device-independent way to run GPGPU code on Android?

Is RenderScript the only device-independent way to run GPGPU code on Android ?
I don't count Tegra as there is only few phones that have it.

RenderScript is the official Android compute platform. As a result it will be on all Android devices. It was designed specifically to address the problem of running one code base across many different devices.

Well, using RenderScript doesn't necessarily mean that your code will run on the GPU. It might also use the CPU and (hopefully) parallelize tasks on several CPU cores and use CPU vector instructions. But as far as I know, you can never be sure about that and the decision process is kind of a blackbox.
If you want to make sure that your code runs on the GPU, you can "simulate" some GPGPU functions with OpenGL ES 2.0 shaders. This will run on all devices that support OpenGL ES 2.0. It depends on what you want to do, but for example many image processing functions can be implemented very efficiently this way. There is a library called ogles_gpgpu that provides an architecture for GPGPU on Android and iOS systems: https://github.com/internaut/ogles_gpgpu
OpenGL ES 3.1 also supports "Compute Shaders" but few devices support this, yet.

What's the Android's Renderscript equivalent for iOS and Windows Phone?

Renderscript is an Android computation engine that lets you use CPU/GPU native hardware acceleration in order to boost applications, for example in image processing and computer vision algorithms.
Is there a similar thing in iOS and Windows Phone 7/8?

The RenderScript compatibility library is designed to compile for most any posix system. It would be very easy to get it running on other platforms.

I can't speak for Windows Phone but on iOS it would be vImage running on the Accelerate Framework. Just like Renderscript, it is dynamically optimized for the CPU on the target platform.
vImage optimizes image processing by using the CPU’s vector processor.
If a vector processor is not available, vImage uses the next best
available option. This framework allows you to reap the benefits of
vector processors without the need to write vectorized code.
https://developer.apple.com/library/mac/documentation/performance/Conceptual/vImage/Introduction/Introduction.html

I can't speak for Windows Phone but on iOS it would be Apple Metal, its language specification being almost same as renderscript c99.

For iOS it is the newly introduced swift I guess.
Maybe it is worth to try it out, but I'm not an iOS developer so I can't say anything about its performance, but the demos on the WWDC looked promising. Also instead of Renderscript Swift seemes to be designed for graphics, the Renderscript soppurt for graphics has been deprecated and Renderscript turned more into a general computation framework (which of course can be used as a backend for graphic calculations).
https://developer.apple.com/library/prerelease/ios/documentation/swift/conceptual/swift_programming_language/TheBasics.html

Is it possible to program GPU for Android

I am now programming on Android and I wonder whether we can use GPGPU for Android now? I once heard that Renderscript can potentially execute on GPGPU in the future. But I wonder whether it is possible for us to programming on GPGPU now? And if it is possible for me to program on the Android GPGPU, where can I find some tutorials or sample programs? Thank you for your help and suggestions.
Up till now I know that the OpenGL ES library was now accelerated use GPU, but I want to use the GPU for computing. What I want to do is to accelerate computing so that I hope to use some libraries of APIs such as OpenCL.

2021-April Update
Google has announced deprecation of the RenderScript API in favor of Vulkan with Android 12.
The option for manufacturers to include the Vulkan API was made available in Android 7.0 Compatibility Definition Document - 3.3.1.1. Graphic Libraries.
Original Answer
Actually Renderscript Compute doesn't use the GPU at this time, but is designed for it
From Romain Guy who works on the Android platform:
Renderscript Compute is currently CPU bound but with the for_each construct it will take advantage of multiple cores immediately
Renderscript Compute was designed to run on the GPU and/or the CPU
Renderscript Compute avoids having to write JNI code and gives you architecture independent, high performance results
Renderscript Compute can, as of Android 4.1, benefit from SIMD optimizations (NEON on ARM)
https://groups.google.com/d/msg/android-developers/m194NFf_ZqA/Whq4qWisv5MJ

yes , it is possible .
you can use either renderscript or opengGL ES 2.0 .
renderscript is available on android 3.0 and above , and openGL ES 2.0 is available on about 95% of the devices.

As of Android 4.2, Renderscript can involve GPU in computations (in certain cases).
More information here: http://android-developers.blogspot.com/2013/01/evolution-of-renderscript-performance.html
As I understand, ScriptIntrinsic subclasses are well-optimized to run on GPU on compatible hardware (for example, Nexus10 with Mali T604). Documentation:
http://developer.android.com/reference/android/renderscript/ScriptIntrinsic.html
Of course you can decide to use OpenCL, but Renderscript is guaranteed (by Google, being a part of Android itself) to be running even on hardware which doesn't support GPGPU computation and will use any other available acceleration means supported by hardware it is running on.

There are several options: You can use OpenGL ES 2.0, which is supported by almost all devices but has limited functionality for GPGPU. You can use OpenGL ES 3.0, with which you can do much more in terms of GPU processing. Or you can use RenderScript, but this is platform-specific and furthermore does not give you any influence on whether your algorithms run on the GPU or the CPU. A summary about this topic can be found in this master's thesis: Parallel Computing for Digital Signal Processing on Mobile Device GPUs.
You should also check out ogles_gpgpu, which allows GPGPU via OpenGL ES 2.0 on Android and iOS.

Performance of image processing algorithms over android smartphones

I am looking forward to start a project that will use OCR , Object tracking and other Image processing algorithms on Android and I want to accelerate these algorithms using external hardware accelerators on FPGA using the Open Accessory API.
Do Image processing apps perform bad and needs custom hardware for acceleration ? Is there a resource to know about performance of image processing algorithms on smart phones and embedded systems without writing one ?

It's only viable to do optimization after you have done measurements for your particular case.
If you need HW acceleration you might want to check out renderscript. It gives you access to GPU hardware to perform generic computations.

JavaCV offers a number of image processing algorithms. It is basically a Java wrapper for OpenCV. I found this post regarding OpenCV and OCR: https://stackoverflow.com/questions/1284214/simple-ocr-programming-tutorials-articles. Performance really depends on the size of the image and processor on the device. Not sure about using a FPGA. Have you considered using the "cloud" to offload processing?

You can use OpenCV for image processing in Android. The best tutorial I can find is OpenCV setup on Eclipse. However if you do image processing in Java the results will be slow, so use second part of the tutorial to program in C then using JNI make the code run for android.
But still a lot of image re sizing and defining region of interest is needed to make the program run in real time if you do object recognition.