Suresh Kannaiyan

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Face recognition is an interesting and a challenging problem that has been widely studied in the field of pattern recognition and computer vision. It has many applications such as biometric authentication, video surveillance, and others. In the past decade, several methods for face recognition were proposed. However, these methods suffer from pose and(More)
In the past, several automatic video summarization systems had been proposed to generate video summary. However, a generic video summary that is generated based only on audio, visual and textual saliencies will not satisfy every user. This paper proposes a novel system for generating semantically meaningful personalized video summaries, which are tailored(More)
This paper presents a new methodology for image description to extract discriminative features from images, that are robust and invariant to illumination changes. The proposed approach describes the image features using multisupport interest regions. The features from multisupport regions are extracted after transforming each interest region into log polar(More)
In this paper, a novel mechanism for generating user-based video abstracts has been proposed. Initially, video experts (operators) score the video frames based on the different modalities contextual information. Later, a two-dimensional matrix that stores the relativity scores of each video scene and a number of pre-defined semantic categories are(More)
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