Why megapixel ?

More pixels mean more detail is captured from a scene. Just like human eye is better able to appreciate images and videos at higher resolution, video and image processing software has more data and hence more potentially useful information that it can extract from higher resolution images. Let’s take a simple example of a face detection analytics. Face detection algorithms require faces to be at least 24x24 pixels in the image. Now consider a 640x480 (VGA resolution) sensor. Say, there is a 6 ft tall human at a distance of 15 feet from this sensor. Assuming that the field of view of this sensor is 90 degrees, the coverage at 15 distance from the sensor will be a 30ft x 30ft plane. This means that 640 pixels will cover 30 ft in width and 480 pixels will cover 30 ft in height. 1 ft high face (hello long face!) will hence get 480/30 pixels which is equal to 16 pixels in height. Clearly detecting faces at a distance of more than 15 feet will be impossible with a VGA resolution sensor based analytics. Instead if we were to use 1 or 2 megapixel sensor, it will be possible to do face detection at larger distances. In fact I will leave this as a simple exercise for our readers.

As you can see there is a direct correlation between the distance you can cover from a sensor for the purpose of analytics and the resolution of the camera as analytics require a minimum number of pixels to compute discriminating features relevant for those analytics. In a nutshell, megapixel analytics provide better solutions to existing problems and open up more possibilities for other applications areas – some of which we will cover in line with our product roadmap.

The next questions is why do we need to do this at the edge ? We will cover that in the next post.


Vijay

Let the blogging begin !!

We will use this blog to share our experiences, learnings, product direction and challenges with our audience in as much detail as possible. The goal of the blog is to provide material of interest in a short and simple fashion that allows us to create a conversation with our community. It is the explorer in us that makes us push the boundaries of current technology. We know that we ride on the shoulders of the giants before us and we intend to provide that small step forward for those who work with us and will work after us. So this is a blog for the our customers, partners, users, competitors, teachers, students and the rest.

As a Company we are focussed on developing megapixel intelligent video products and components on embedded platforms. The challenges that we intend to address start with a specific problem to be solved like traditional surveillance centric analytics. We address these algorithmic challenges using state-of-the-art techniques available and improving them at an alogorithm level with newer ideas, in line with performance goals. We then port this into our embedded platform leveraging a wide range of embedded optimization techniques including

1. Tools provided by DSP for efficient memory and CPU management,
2. Using cascading set of filters on video frames that progressively apply on a narrower region of the image (less pixels to work with)
3. Using image and data representations in data structures that improve performance of specific algorithms on the embedded platform
4. Implementing some of the core image processing functions in assembly language

At each step the implementation is tested against the performance metrics that are set for the problem at hand. We have been working on this for some time and we continue to make huge improvements in our time to market to bring in new implementations to market. So let the journey begin...

Vijay