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Jan H. Elenbaas

Researcher at Philips

Publications -  13
Citations -  891

Jan H. Elenbaas is an academic researcher from Philips. The author has contributed to research in topics: Image processing & Video compression picture types. The author has an hindex of 11, co-authored 13 publications receiving 891 citations.

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Patent

Apparatus and method for locating a commercial disposed within a video data stream

TL;DR: In this article, a frame grab thread is used to acquire frames from an input data stream to be analyzed by a cut detector thread and a filter thread, and a commercial detection thread determines whether a commercial has occurred from data created by the cut detector and the filter thread stored in a memory.
Patent

Video stream classifiable symbol isolation method and system

TL;DR: In this paper, an image processing device and method for classifying symbols relies on a connected-component technique for isolating symbol regions, which form connected components from an image derived by the application of an edge detection filter.
Patent

Method and system for analyzing video content using detected text in video frames

TL;DR: In this paper, a video processing device for searching video streams for one or more user-selected image text attributes is presented. But the video processing devices are limited in their ability to detect and extract image text from video frames, determining attributes of the extracted image text, comparing the extracted text attributes and the user-selectable image text features, and modifying, transferring, and labeling at least a portion of the video stream in accordance with user commands.
Patent

Significant scene detection and frame filtering for a visual indexing system using dynamic thresholds

TL;DR: A keyframe filtering process filters out less desired frames including unicolor frames, or those frames having the same object as a primary focus or one primary focus as discussed by the authors, based on a threshold which is set based on the category of the video.
Patent

Personalized news retrieval system

TL;DR: In this paper, a video retrieval system is presented that allows a user to quickly and easily select and receive stories of interest from a video stream, which is particularly well suited for targeted news retrieval.