Samsung Electronics Co., Ltd.

David Tsidkiahu

Nathan Henri Levy

Omer Shabtai

Ishay Goldin

Ran Vitek

Alexandra Dana

Netanel Stein

Yotam Platner

Tal Heller

Alon Intrater

Yaron Ukrainitz

Zuf Pilosof

Techniques and apparatuses enabling high accuracy video object detection using reduced system resource requirements (e.g., reduced computational load, shallower neural network designs, etc.) are described. For example, a search domain of an object detection scheme (e.g., a target object class, a target object size, a target object rotation angle, etc.) may be separated into subdomains (e.g., such as subdomains of object classes, subdomains of object sizes, subdomains object rotation angles, etc.). Specialized, subdomain-level object detection/segmentation tasks may then be separated across sequential video frames. As such, different subdomain-level processing techniques (e.g., via specialized neural networks) may be implemented across different frames of a video sequence. Moreover, redundancy information of consecutive video frames may be leveraged, such that specialized object detection tasks combined with visual object tracking across consecutive frames may enable more efficient (e.g., more accurate, less computationally intensive, etc.) full domain object detection and object segmentation schemes.

Fast object detection in video via scale separation

Growing community of inventors

Tel Aviv, Israel

David Tsidkiahu