The biggest news in this week's AR/VR circle is Nvidia's GTC conference in Beijing. At the conference, not only did many VR-related companies come online, Nvidia also demonstrated its great support for VR development. Another big news is the company AR, a company called Snapdragon Technology. In the case of a sluggish financing market, the A+ round actually got 50 million in financing. Of course, we will not miss the apple that has just opened the conference. Although they currently do not have any AR/VR equipment, they are fully prepared. Here's the immersive Weekly magazine that we organized for everyone this week:
Xiaolong Science and Technology Shi Xiaogang: Financing in the Winter, for the Far Future of ARIn the AR/VR field, everyone is optimistic about AR (Augmented Reality) and even VR (Virtual Reality), but AR is not mature enough and its prospects are not clear. In this environment, a new financing news is even more worthy of attention.
Snapdragon has just announced the acquisition of a 50 million yuan A+ round of financing from BOE Leading Investment. Prior to this, the company had obtained tens of millions of yuan in round A financing from Lixin Precision Leading Investment in early 2016. For this company established in June of 15 years, three rounds of financing for angels, A and A+ were completed within one year, and the speed was still very fast.
BOE has been betting on the AR field. In fact, the company invested in the famous AR startup company Meta in the world as early as 2014. Shi Xiaogang believes that the strategic fit of the two has contributed to investment. However, BOE can provide more than this, he said the following three points are also the reasons for the investment.
First, BOE has a large piece of business that is the OEM of the whole machine, and the two sides will form a deep cooperation on the whole OEM. For start-up companies, there is a huge gap between R&D products and production products, and many product skip tickets are also unable to cross this gap. In fact, this product that Xiaolong already sells is the leader of the previous round of investment.
Secondly, Xiaolong and BOE will also have strong cooperation in the R&D of the whole machine. With the latter's strong supplier resources and R&D resources, they can help the products to be smaller and apply more advanced technologies.
3. At present, sales of AR glasses at the C-end are difficult to do, while BOE has a government background and has many 2B channels. There are many market resources in this area.
Social VR will become the next big thing in the entertainment industry? Industry analystsTo say that the industry is most enthusiastic about the VR industry, the non-video game industry must be.
In the past two or three years, media reports on teenagers wearing VR helmets and using VR motion controllers completely immersed in the virtual world have been overwhelming. Although, like others, I also believe that VR technology will undoubtedly change and redefine what we currently know about video games, I firmly believe that VR technology can do more than that.
Why do you say that Apple is doing VR? Evidence is hereAs an electronics company, Apple's strategy has always been to wait for the market to mature before joining the battle, and then create the ideal Apple products for the market. Given the current size of the AR/VR market and its usage scenarios for a wide range of users, it is too early to implement this plan.
Even so, this does not mean that Apple is not active at all in AR/VR research and development. In fact, in the past few years, this company has been expanding its own number of experts in this field, it is very likely that Apple has now established a considerable team to explore how this new technology can be used in their own On the product.
Let 980 run out of 1080 and Qixin Yiwei launches new VR eye control | GTC China 2016At the GTC China 2016 held at Nvidia on September 13th, Qixin Yiwei, a domestic startup with eye tracking technology, released the first eye-control peripheral for HTC Vive and applied this technology to VR. Above.
This product, known as the world's first VR eye accessory, brings two major functions to VR: eye-control interaction and gaze point rendering. The former brings new interaction to VR, while the latter enhances the GPU through new rendering methods. Rendering efficiency.
According to reports, the power consumption of this product with monocular tracking is less than 500mW. If it is working in power saving mode, it will be lower. The request for processing performance, Huang Tongbing, said that Qualcomm's Xiaolong 820 is supportive, and "there is no problem with the mainstream."
However, this product will not be sold as a consumer version. It is expected to land in JD.com in October and sell for around RMB 3,000, mainly for developers. The consumer-oriented products will be launched in cooperation with helmet manufacturers and built into the latter products. The specific product launch time is still to be determined, but it is learned that Qualcomm's all-in-one solution will focus on pushing this technology, and domestic friends and 3Glasses are also very active.
VR developers, Nvidia prepares you for pickpockets | GTC China 2016Nvidia also opened the GTC from the United States to Beijing, and opened a separate forum for VR. Since the theme of the forum was “Made in China 2025 and Virtual Realityâ€, we heard more about the application of VR technology at the industrial level. The use of these technologies is backed by Nvidia's support for graphics processing, especially the development suite VRWorks, which is designed for VR developers.
Behind Intel's acquisition of Movidius: Why do we need a dedicated CV processing chip?At the world’s top computer vision conference, according to incomplete statistics, more than 70% of articles are related to deep learning. In the areas of image classification, object detection, semantic segmentation, etc., the results of deep learning have taken a big lead. Traditional algorithm. According to Microsoft Asia Research Institute, many scholars have given their own solutions based on deep learning even in areas where traditional methods such as 3D vision and low-level image processing are relatively mainstream.
Taking gesture recognition as an example, traditional recognition schemes are mostly based on color spaces such as RGB, HSV, and YCrBr. However, these algorithms cannot exclude the interference of skin-colored objects and black skin on the recognition accuracy. Some algorithms also perform recognition by extracting the opponent contour features, such as the HoG+SVM classification recognition method, but they still cannot improve the recognition accuracy under the conditions of dim light and backlight. However, with deep learning, such as training a large number of marked gesture image data through R-CNN, the resulting model is much better than traditional solutions when dealing with gesture recognition problems with complex backgrounds and dark light environments.
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