Anonymous FTP-able Image Data

Image database used in shape-based retrieval experiments: pictures.tar.gz

This tar file contains 86 color images of animals (rabbits and fish), and 63 monochrome images of hand tools. Support mask images are also provided. These images were used for experiments reported in:
Sclaroff, S., Deformable Prototypes for Encoding Shape Categories in Image Databases, Pattern Recognition, 30(4):627-642, Apr., 1997.

Images databases used in deformable shape-based segmentation and retreival experiments

These are images databases used in experimental evaluation of deformable color region grouping methods for shape-based retrieval. The data was used in evaluating the system described in: Liu, L., and Sclaroff, S., Deformable Shape Detection and Description via Model-Based Region Grouping, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, (CVPR), June, 1999.

Over 70 video sequences and ground truth used in evaluation of 3D head tracking

The directories contain over 70 extended video sequences used in head tracking experiments. Ground truth for position and orientation of the head was acquired using a magnetic sensor (Flock of Birds sensor). The data was used in evaluating the system described in: La Cascia, M., and Sclaroff, S., Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Robust Registration of Texture-Mapped 3D Models, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI),Vol. 22, No. 4, pp 322-336, 2000.

Video sequences of American Sign Language (ASL)

Video of ASL sentences, taken with multiple synchronized digital cameras to capture different views of the subject. Collected in The National Center for Sign Language and Gesture Resources.

Labeled video sequences used as ground truth in skin color segmentation experiments

To evaluate the performance of our color segmentation system, we collected a set of 21 video sequences from nine popular DVD movies. Collected sequences vary in length from 50 to 350 frames; most, however, are in the 70 to 100 frame range. All experimental sequences were hand-labeled to provide the ground truth data for algorithm performance verification. This data was used in evaluating the system described in: Sigal, L., and Sclaroff, S., Estimation and Prediction of Evolving Color Distributions for Skin Segmentation Under Varying Illumination Proc. IEEE Conf. on Computer Vision and Pattern Recognition, (CVPR), June, 2000.

Hand image database with ground truth

This dataset contains 107,328 images of a realistic computer graphics rendering of realistic human hand model. Ground truth for each image is available, thus enabling quantitative evaluation of articulated pose esimtation algorithms. More than 200 real images of hands are also distributed with this dataset. The dataset was used in evaluating the system described in: Vassilis Athitsos and Stan Sclaroff, Estimating 3D Hand Pose From a Cluttered Image, Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Vol. 2, pp 432-439, 2003.

Dynamic background sequences

This dataset contains videos used in testing the dynamic background modeling system described in: Jing Zhong and Stan Sclaroff, Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter, Proc. International Conf. on Computer Vision (ICCV), 2003.

Hand shape image data

These datasets contain hand shape images used in evaluation of algorithms described in: Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, and Stan Sclaroff, Multiplicative Kernels: Object Detection, Segmentation, and Pose Estimation, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, (CVPR), June, 2008.

Multi-face tracking test videos

This dataset contains videos used in testing tracking of multiple faces in video using the multiplicative kernel framework, used for evaluation in: Quan Yuan, Ashwin Thangali, Vitaly Ablavsky and Stan Sclaroff, Learning a Family of Detectors via Multiplicative Kernels, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 33, No. 3, pp 514-530, 2011.

Vehicle tracking sequences

This dataset contains videos used in testing tracking using the multiplicative kernel framework, used for evaluation in: Quan Yuan, Ashwin Thangali, Vitaly Ablavsky and Stan Sclaroff, Learning a Family of Detectors via Multiplicative Kernels , IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 33, No. 3, pp 514-530, 2011.

 

Layered Graphical Models dataset

This dataset contains videos used in testing tracking using the layers of graphical models framework, used for evaluation in: Vitaly Ablavsky and Stan Sclaroff, Layered Graphical Models for Tracking Partially-Occluded Objects , IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 33(9):1758-1775, 2011.