ADAS (advanced driver assistance systems) are rapidly being incorporated into automobiles and other vehicles, as products unveiled at January's North American International Auto Show in Detroit, Michigan made clear. Just a few short years ago, passive collision warning and active collision avoidance features were restricted to luxury models from luxury manufacturers. Now, even mass-market car suppliers are incorporating ADAS capabilities into their high-end and mainstream vehicles.
In order for
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As computer vision is deployed into a variety of new applications, driven by the emergence of powerful, low-cost, and energy-efficient processors, companies need to find ways to squeeze demanding vision processing algorithms into size-, weight-, power, and cost-constrained systems. Fortunately for its clients, BDTI's skill in benchmarking has armed it with unique skill in optimizing software to best exploit processor capabilities. It's also provided BDTI with an in-depth understanding of the
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Just prior to the 2014 Consumer Electronics Show, Imagination Technologies unveiled its first computer vision processor offering with the announcement of the Raptor core architecture, the first product iteration of which was released at the February 2014 Mobile World Congress. Now, the company is more fully embracing computer vision requirements with its two new PowerVR Series7XT Plus GPU cores. And, reading between the lines of a recent briefing, Imagination Technologies continues to seriously
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Automobile-based processing intelligence, both in the form of fully autonomous vehicles and more modest ADAS (Advanced Driver Assistance Systems), garnered exclusive billing in NVIDIA's keynote and booth at this year's Consumer Electronics Show, held last month in Las Vegas, Nevada. The information presented highlighted the growing importance of automotive applications not only to NVIDIA and its semiconductor competitors, but also to their shared customers as well as to their customers, i.e.
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Hear the words "high volume DSP market" and you might automatically think of "mobile phones". And you'd be right; recent estimates peg quarterly worldwide mobile phone shipments approaching half a trillion units, with smartphones (which often contain multiple DSP cores) representing three-quarters of that amount. However, CEVA believes that in the not-too-distant future, alternative markets with similar cellular connectivity needs—wearables, connected vehicles, and a diversity of IoT devices—
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In 2013, Tensilica (subsequently acquired by Cadence) released its second-generation image processing IP core, the IVP, which also supported modest computer vision capabilities (Figure 1). One year later came the IVP-EP, which supported increased data precision flexibility, boosting overall performance in many applications and therefore further expanding the core's vision processing function reach. And in October of this year, Cadence further extended the product line, unveiling its latest
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Algorithms are the essence of digital signal processing; they are the mathematical "recipes" that transform signals in useful ways. Companies developing new algorithms, or considering purchasing or licensing algorithms, often need to assess whether an algorithm will fit within their processing budget—and thereby within their cost and power consumption targets.
But estimating an algorithm's processing load can be difficult if the algorithm has not already been carefully mapped onto the target
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The decreasing cost-per-transistor delivered by modern semiconductor processes means that a number of previously rare embedded processor options are now increasingly common. This trend includes floating-point coprocessors, which are especially useful when migrating code originally developed on a PC to an embedded system. Recall that floating-point support on the PC wasn't a "given" until the first 1993-era Pentium processor-based systems hit the scene; earlier i486 CPUs offered the integrated
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In September, Freescale announced its acquisition of computer vision processor IP supplier CogniVue. BDTI discussed the news with Matt Johnson, Vice President and General Manager of Freescale's Automotive MCU division, which instigated the transaction. The two companies had closely collaborated for the past several years, so the purchase wasn't a complete surprise. Still, the interview produced a number of interesting insights. Also in attendance was Simon Morris, former CEO of CogniVue (now a
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A growing number of products are incorporating computer vision capabilities. This, in turn, has led to rapid growth in the number of processors being offered for vision applications. Selecting the best processor (whether a chip for use in a system design, or an IP core for use in an SoC) is challenging, for several reasons.
First, these processors use very diverse architecture approaches, which makes it tough to compare them. Second, because vision applications and algorithms are also quite
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