Method and Apparatus for Detecting, Tracking, Recognizing, and Categorizing Objects and Scenes from Video
Feature selection and tracking are performed in real-time Improved baseline algorithms in terms of performance accuracy and robustness Lower computational costs
Interactive mobile applications including gaming, video editing, and image processing Security applications including image recognition and image data filtering
Researchers at UCLA have developed an end-to-end visual recognition system that allows a mobile user to select objects in their own real-time video for future visual recognition by the system. The method categorizes and tracks selected objects by selecting multiple feature points corresponding to translational, similarity, or affine reference frames, and processes the information with optimized algorithms. The system is then able to recall the selected objects in future real-time video streams.
信息和通信技术/电信
多媒体
8717437
State Of Development Researchers have developed a working prototype. To see the prototype in action, please follow this link on Youtube: Background Almost all smart phones have built in video cameras for taking photographs and recording videos. Innovative applications have made it possible for users to enjoy the footage in many new ways. However, there are many more avenues to explore with built-in video cameras. In particular, current devices are not equipped to recognize, track, and process objects captured in a video stream. Such information is extremely useful for the future of gaming, security, video editing, and image processing. Additional Technologies by these Inventors Tech ID/UC Case 22256/2011-479-0 Related Cases 2011-479-0
http://www.youtube.com/watch?v=cMv-McHw660&feature=player_embedded
美国
