Shengzhe Li

Learn More
Understanding the difficulty of a dataset is of primary importance when it comes to testing and evaluating fingerprint recognition systems or algorithms because the evaluation result is dependent on the dataset. Proposed in this paper is a general framework of assessing the level of difficulty of fingerprint datasets based on quantitative measurements of(More)
0020-0255/$ see front matter 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ins.2013.05.025 ⇑ Corresponding author. Tel.: +82 10 6336 7385. E-mail addresses: szli@vision.inha.ac.kr (S. Li), hikim@inha.ac.kr (H. Kim), cljin@sdu.edu.cn (C. Jin), elliott@purdue.edu (S. Elliott), mmj8 hotmail.com (M. Ma). Shengzhe Li , Hakil Kim a,⇑,(More)
Real-time detection of fire flame in video scenes from a surveillance camera offers early warning to ensure prompt reaction to devastating fire hazards. Many existing fire detection methods based on computer vision technology have achieved high detection rates, but often with unacceptably high falsealarm rates. This paper presents a reliable visual analysis(More)
Human action recognition has become an important research topic in computer vision area recently due to many applications in the real world, such as video surveillance, video retrieval, video analysis, and human-computer interaction. The goal of this paper is to evaluate descriptors which have recently been used in action recognition, namely Histogram of(More)
This paper proposes a real-time fire detection algorithm for video surveillance. Firstly, candidate fire regions (CFRs) are detected using modified conventional methods, that is, the detection of moving regions and fire-colored pixels. In order to avoid false alarms, effective color and shape-based features are extracted from CFRs. Then, the set of features(More)