Tina - The only difference I see between the 7962 and the 7690 is the MIPI interface and support for 50/60Hz illumination compensation. Regardless, I think they would have gotten more milage from a better imager. Perhaps a future rev of the cube design? Incidentally, I only noticed this because I'm working on a similar compact imager concept, except that my system does passive stereo processing to generate depth information. Of course, it wouldn't be the same small form factor, but the all-in-one concept is the same. It's good to see products like this come to market.
btwolfe - Just to clarify, the SmartVue development camera module uses OV7962 a wide dynamic range VGA sensor (not 7690). The CV2201 Image Cognition Processor in the camera (the brains so to speak) is sensor-agnostic and can interface to a number of different sensors including megapixel.
Seems like a nice development package, but I wonder why they chose the 7690 imager instead of a more capable one like the OmniVision 5642. I've used the 7690 and it's image quality is marginal at best, whereas the 5642 is razor sharp. Perhaps the ARM processor couldn't process anything better than VGA, but the 7690 built-in optics are subpar.
Charles you are spot on. In fact CogniVue has demonstrations for the following driver assistance systems: lane departure warning, forward collision avoidance and blind spot detection.
Readers can check out our video demos on YouTube at the following link:
Engineers from the auto industry will take a hard look at this technology, if they aren't looking already. Lane keeping, adaptive cruise control, collision avoidance, rear-view assist, traffic sign recognition, and blind spot detection are only a few of the applications that might use this. It's said that middle- and upper-class vehicles could soon contain as many as 15 cameras apiece.
Sounds like a very powerful device. Nice to see more advanced activity in both intelligent vision and embedeed vision technologies. From my perspective, people who want to apply vision don't want to get bogged down in coding algorithms; they just want to use them to accomplish something. Placing everything--hardware and software--in an easy to use package should give designers a quick start. Nicely done.
Jon - Yes you are correct that the CV2201 Image Cognition Processor has 2 ARM9s, but the real performance comes from programming the parallel processing engine (APEX). From a software standpoint, we provide developers with an SDK, APEX tools (compiler&simulator for those looking to develop their own proprietary algorithmic functions executing on the APEX), Toolkits: Video/Audio Player-Recorder toolkit, Image Processing Toolkit (includes pre-optimized kernels, primitives and algorithmic components executing on APEX for advanced image cognition applications), Camera calibration toolkit, and complete Applications. We're in field-trials now with an aftermarket automotive smart backup camera appliccation - a single camera doing dewarp, perspective correction, object detection, distance estimation and graphic overlay - rendering the data to the driver-side display in real-time to prevent backover accidents. It's another application that is taking off in a big way with automotive OEMs and aftermarket suppliers. Re ARM debugging - we support Lauterbach Trace32 JTAG debugger in addition to Amontec JTAGkey2 and Segger J-Link debuggers.
Actually, the chip has two ARM9 processors; one associated with the image-processing components, and one "on the side" for what I assume are general-purpose operations. Cognivue provides a development kit and a software development suite of tools, but the company's Web site doesn't supply more than a one-page summary of the tools available for developers. Still, that second ARM9 processor looks like a good way to customize the chip to many applications. The chip has many unused I/O pins and internal peripherals, too. ARM has designed an excellent debugging and trace section for processor licensees. I'd like to know if the Cognivue chip makes them available for the embedded ARM9 processors. Looks like the software "kit" includes an RTOS.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
Using Siemens NX software, a team of engineering students from the University of Michigan built an electric vehicle and raced in the 2013 Bridgestone World Solar Challenge. One of those students blogged for Design News throughout the race.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.