The application of artificial intelligence to interpret and act on visual data can be used in a variety of fields, including child development, social media networks, and web analytics. For example, Oakland, California-based Captricity's software interprets handwritten documents, while Affectiva, a company begun at the Massachusetts Institute of Technology, focuses on analyzing emotion in facial expressions.

Why it's hot: The industry is being driven by a rapid uptick in machine vision and artificial intelligence capabilities as well as increasing interest in the commercialization of drones, autonomous cars, and other robotics applications.

What's required: Computer vision entrepreneurs must have a high level of technical know-how, likely with an engineering degree.

Barriers to entry: This industry requires a high level of technical understanding to create software that collects and interprets visual data. Depending on the application, it may also require deep knowledge of another industry. For example, Palo Alto, California-based Cape Analytics, which raised $14 million in its first round of venture funding in November, applies computer vision and machine learning to automate property underwriting for insurance companies.

The downside: The field is sure to get more competitive, and its highly technical nature will be a challenge to new entrants.

Competition: Startups in computer vision abound, but the industry has not yet produced a clear market leader. Notable companies include navigation system Zurich Eye and eye-tracking tech startup the Eye Tribe--both of which were acquired by Facebook's virtual reality arm Oculus--and Terraloupe, an aerial image analytics startup.

Growth: In 2016, venture capital funding in computer vision reached $522 million across 69 deals globally, compared with $186 million across 47 deals in 2015 and $44 million across 15 deals in 2012, according to CB Insights.

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