亚洲知识产权资讯网为知识产权业界提供一个一站式网上交易平台，协助业界发掘知识产权贸易商机，并与环球知识产权业界建立联系。无论你是知识产权拥有者正在出售您的知识产权，或是制造商需要购买技术以提高操作效能，又或是知识产权配套服务供应商，你将会从本网站发掘到有用的知识产权贸易资讯。

返回搜索结果

Sentence Directed Video Object Codetection

总结: Researchers at Purdue University have developed a new method of video object codetection using the audio and visual cues in the video to help interpret and detect objects. This technology allows for video object detection without the need for object pre-learning. Using an algorithm that first generates sentences that describe an object's appearance/movement in the video by comparing subtle differences against a static background, it produces and displays a bounding box around an object while it is present in the video field. Using this technology, object detection is more robust, allowing for the detection of more objects, faster, and more accurately than ever before.

技术优势: Objects do not need to be pre-learned Increased accuracy Detects nearly any sized object Detects multiple objects simultaneously Works with fast object movement and motion blur

技术应用: Surveillance Security Autonomous vehicles Facial recognition Computer vision Medical imaging Robotics

*Background: Video object detection is a broad field with many applications ranging from self-driving cars to security surveillance. Video object codetection normally requires the pre-learning of objects before they can be detected. Pre-learning is a problem with many applications given it is not possible to pre-learn all potential scenarios. In addition, most of the work in object detection focuses on still images, which is simpler than the changing and moving viewpoints found in videos.

*Web Links: Purdue Office of Technology CommercializationPurdueInnovation and EntrepreneurshipJeffrey SiskindPurdue Electrical and Computer Engineering

欲了解更多信息，请点击这里