Motorbikes (Side) dataset. Collected by undergrads at Caltech (Feb '01) from the web. 826 images of motorbikes from the side. JPEG format. ImageData.mat is a MATLAB file containing the variable SubDir_Data which is an 8 x 826 matrix. Each column of this matrix hold the coordinates of the bike within the image, in the form: [x_bot_left y_bot_left...

Car dataset taken by Markus Weber, Caltech PhD student under Pietro Perona. 126 images of cars from the rear. Approximate scale normalisation. JPEG format. Taken in the Caltech parking lots. 896 x 592 pixels.

The dataset contains images of people collected from the web by typing common given names into Google Image Search. The coordinates of the eyes, the nose and the center of the mouth for each frontal face are provided in a ground truth file. This information can be used to align and crop the human faces or as a ground truth for a face detection a...

This dataset contains random objects from home. The objects are taken mostly from kitchen, bathroom and living-room environments. Each directory ("Train" and "Test") contains a subdirectory named 'Gtruth/', containing ground truth .mat files. The .mat files contain a variable 'outline'. For training images, 'outline' contains the corners of a bo...

Pasadena Houses 2000241 photographs of Pasadena houses collected by C. Helle and P. Perona in Summer 2000. The size of each image is 1760x1168. (c) California Institute of Technology.

******************************************************************************   Caltech Vision Group Signature Data version 1.0*   (c) Mario E. Munich & Pietro Perona*   California Institute of Technology*   Copyright 1998-2002**       In case that this data is used for a publication, please*       cite the following articles:**   @ARTICLE{muni...

A large and well annotated dataset of actions on the current best image dataset for visual recognition, with rich annotations including all the actions performed by each person in the dataset, and the people and objects that are involved in each action, subject's posture and emotion, and high level visual cues such as mutual position and distance.

We introduce a challenging set of 256 object categories containing a total of 30607 images. The original Caltech-101 was collected by choosing a set of object categories, downloading examples from Google Images and then manually screening out all images that did not fit the category. Caltech-256 is collected in a similar manner with several impr...

Car dataset taken by Brad Philip and Paul Updike as part of a Caltech SURF project in summer 2001. 526 images of cars from the rear. 360 x 240 pixels. No scale normalisation. JPEG format. Quite a few repeat images. Taken on the freeways of southern California.

Contains images and human response data for a visual classification task on three datasets. Datasets are intended to serve as benchmark for visual knowledge tracing algorithms.