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Kai (Alex) Qin
My research interests include pattern recognition, image processing, computer vision, machine learning, evolutionary computation, remote sensing data analysis, biometrics and bioinformatics.
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Zhijie Wang
My current research focuses on Image Processing and Computer Vision, or more specifically, automated image and video analysis through detection, tracking and segmentation methods.
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VIP-HARPET Dataset
The VIP-HARPET dataset is a dataset of hockey action recognition and pose estimation in temporal space (HARPET) which consists of sequences of 3 images. Each sequence is pose annotated with respective classes labeled.
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VIP-HARPE Dataset
The VIP-HARPE is a custom dataset of static images for hockey action recognition and pose estimation (HARPE). The dataset consists of images of hand annotated images of 18 joints locations which include, head, thorax, hips, elbows, stick, etc., and grouped into classes such as skating, firm-feet, shooting and passing.
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VIP-Sal Dataset
The VIP-Sal is a custom dataset of objects against a non-uniform background, under 3 drastic lighting conditions. Ground truth was obtained through manual segmentation.
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VIP-LowLight Dataset
The VIP-LowLight dataset is a set of natural images captured in very low-light conditions. The dynamic range of the images were scaled to show the image content and the corresponding amplification of the ISO noise.
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VIP Visual Projection Assessment Dataset
The VIP VPA dataset (VPAD) is a dataset for image and video resolution enhancement assessment. The VPAD consists of a set of videos for various movies, documentary, sports, and TV news channels with the presence of moving and text-like regions.
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VIP RGB-D Scene Flow Dataset
Dataset of RGB-D data for scene flow estimation. Ground truth flow is provided.
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VIP Illumination Saliency Dataset
A set of images used for evaluating illumination invariant saliency detection.
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Texture Classification
Texture Classification is the problem of distringuishing between textures, a classic problem in pattern recognition. Since many very sophisticated classifiers exist, the key challenge here is the development of effective features to extract from a given textured image.
