The automotive industry continues to be a hotbed of patent innovation. Activity in camera orientation estimation is driven by driver assistance systems, autonomous vehicles, real-time estimation, and artificial intelligence (AI). The automotive industry is utilizing AI-based and deep learning technologies for camera orientation estimation, aiming to enhance advanced driver assistance systems (ADAS) and autonomous vehicle performance, safety, efficiency, and emissions reduction. In the last three years alone, there have been over 720,000 patents filed and granted in the automotive industry, according to GlobalData’s report on Innovation in automotive: camera orientation estimation. Buy the report here.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilizing and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
300+ innovations will shape the automotive industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the automotive industry using innovation intensity models built on over one million patents, there are 300+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, multi-spark ignition, integrated multi-motor drivetrains and vehicle auxiliary drives are disruptive technologies that are in the early stages of application and should be tracked closely. Solar range extenders, turbocharger shaft bearings, and multi-lamellar clutches are some of the accelerating innovation areas, where adoption has been steadily increasing. Among the maturing innovation areas are auto-transmission lubrication circuits and electroluminscent vehicle displays, which are now well established in the industry.
Innovation S-curve for the automotive industry
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Camera orientation estimation is a key innovation area in automotive
Camera orientation estimation is a process that involves calculating the position and speed of a target object by estimating values based on parallax/transition information. It involves using temporally sequencing taken images to detect a road surface region and to determine pixels that correspond to the road surface region. This way, the estimated value calculation does not consider the pixels corresponding to the road surface region, but rather the other pixels that correspond to the target object.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 1020+ companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of camera orientation estimation.
Key players in camera orientation estimation – a disruptive innovation in the automotive industry
‘Application diversity’ measures the number of applications identified for each patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of countries each patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to camera orientation estimation
Source: GlobalData Patent Analytics
Intel is one of the leading patent filers in camera orientation estimation. The company has developed a system using artificial intelligence to estimate camera orientation in real-time, improving driver assistance systems and autonomous driving. The system offers high accuracy, robustness, and speed, making it a promising development in the automotive industry. Sony and Canon are some other key patent filers in this space.
In terms of application diversity, Sony leads the pack, while Canon and Enlitic stood in the second and third positions, respectively. By means of geographic reach, Enlitic held the top position, followed by Alphabet and NVIDIA.
To further understand the key themes and technologies disrupting the automotive industry, access GlobalData’s latest thematic research report on Automotive.
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