Spectacular videos of embedded vision in action! Provided by the Embedded Vision Alliance http://www.embedded-vision.com/eye-catching-embedded-vision-clips    

From feature descriptors to deep learning: 20 years of computer vision http://quantombone.blogspot.ie/2015/01/from-feature-descriptors-to-deep.html We all know that deep convolutional neural networks have produced some stellar results on object detection and recognition benchmarks in the past two years (2012-2014), so you might…

It’s Time to Relabel the Brain  http://psychsciencenotes.blogspot.ie/2015/01/its-time-to-relabel-brain.html Another day, another study finds that ‘visual’ cortex is activated by something other than information from the eyes: A research team from the Hebrew University of Jerusalem recently demonstrated that the same part…

http://www.movidius.com/our-technology/myriad-2-platform A dedicated vision processing platform Myriad 2 is the industry’s first always-on vision processor. It delivers high-performance computational imaging and visual awareness in severely power-constrained environments. Myriad 2 exhibits a skillful balance between hard-wired and programmable elements. This gives…

Can Machines “See” Using Convolutional Neural Networks? http://www.altera.com/technology/system-design/articles/2015/convolutional-neural-networks.html Convolutional What? “The simplest way to look at CNNs,” explains i-Abra CTO Greg Compton, “is as a way to build a very powerful many-to-one filter.” For instance, you might design a CNN…

Some searching has turned up these public domain datasets http://www.inf.ed.ac.uk/teaching/courses/dme/2014/datasets.html http://www.ee.oulu.fi/~jaska/datasets.html http://mldata.org/repository/data/viewslug/wearable-accelerometers-activity/ http://www-scf.usc.edu/~mizhang/datasets.html In addition we’ve developed an Android app using AppInventor to capture accelerometer and magnetometer data as timeseries in .csv format and gmail it and backend google scripts…

Paper Pdf: http://goo.gl/SdqOl0 Video: https://www.youtube.com/watch?v=KPNwVNQP7jM Source code: https://github.com/plumonito/dtslam