Company Filing History:
Years Active: 2005-2008
Title: The Innovative Contributions of Cynthia E. Daniell
Introduction
Cynthia E. Daniell is a prominent inventor based in Pasadena, CA. She has made significant contributions to the field of motion recognition technology. With a total of 3 patents, her work has advanced the understanding and application of motion detection systems.
Latest Patents
One of her latest patents is a motion recognition system designed to distinguish between human and animal motion. This system includes a moving object detection component, a motion feature extraction component, and a motion feature classification component. The moving object detection component identifies objects within a video sequence and generates a moving object signal. The motion feature extraction component processes this signal to extract features representing the detected object. Finally, the motion feature classification component classifies these features, allowing users to determine whether the object is a human or an animal.
Another notable patent is the recognition algorithm for unknown target rejection based on shape statistics obtained from orthogonal distance functions. This method involves selecting random first chords across the periphery of a target object and utilizing orthogonal second chords to enhance classification accuracy.
Career Highlights
Cynthia has worked with esteemed organizations such as Raytheon Company and HRL Laboratories, LLC. Her experience in these companies has allowed her to develop and refine her innovative ideas in motion recognition technology.
Collaborations
Throughout her career, Cynthia has collaborated with talented individuals, including Qin Jiang and Narayan Srinivasa. These partnerships have contributed to her success and the advancement of her inventions.
Conclusion
Cynthia E. Daniell's work in motion recognition technology exemplifies her innovative spirit and dedication to advancing the field. Her patents reflect her expertise and commitment to creating solutions that enhance our understanding of motion detection.