Real-time Scene Identification Using Run-length Encoding of Video Feature Sequences

Akio Nagasaka; Takafumi Miyatake

doi:10.20965/jrm.1999.p0098

single-rb.php

« previous

JRM Vol.11 No.2 pp. 98-103

doi: 10.20965/jrm.1999.p0098

(1999)

Paper:

Views over last 60 days: 391

Real-time Scene Identification Using Run-length Encoding of Video Feature Sequences

Akio Nagasaka and Takafumi Miyatake

Central Research laboratory, Hitachi, Ltd. 1-280 Higashi-Koigakubo, Kokubunnji-shi, Tokyo 185-8601, Japan

Received:

August 31, 1998

Accepted:

November 19, 1998

Published:

April 20, 1999

Keywords:

video machine, video identification, indexing, information filtering, real-time processing

Abstract

We propose real-time video scene identification that detects all same scenes in stored videos as the latest freelength scene, compressing the video feature sequence in an average of less than 20 bytes per second to store features for a long time. It takes less than 30ms on the average for a typical personal computer to process 1 newly input fame image even storing more than 24-hour video features. Experiments with TV showed that this method finds correct pairs of the same scenes in real time without error. This becomes the basis for active video recording based on a user’s TV viewing history and for new robotic machine vision for surveillance.

Cite this article as:

A. Nagasaka and T. Miyatake, “Real-time Scene Identification Using Run-length Encoding of Video Feature Sequences,” J. Robot. Mechatron., Vol.11, No.2, pp. 98-103, 1999.

Data files:

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.