The dataset consists of ...
1) Camera-trap dataset for animal detection or animal/non-animal image classification
Related publication: Tekeli, U. and Bastanlar, Y., Elimination of Useless Images from Raw Camera-Trap Data, submitted to Turkish Journal of Electrical Engineering and Computer Sciences.
The dataset consists of more than 100 .avi files and can be downloaded as rar files (~200 MB each) using the link given
2) Fisheye video dataset for vehicle classification
Videos containing cars, vans, motorcycles or pedestrians. Some videos contain more than one object (some with occlusions), they are mentioned in the spreadsheet provided.
Related publication: Baris, I. and Bastanlar, Y., Classification and Tracking of Traffic Scene Objects with Hybrid Camera Systems, IEEE International Transportation Systems Conference (ITSC 2017), 16-19 October 2017, Yokohama, Japan.
The dataset can be downloaded via three different zip files using the links given below.
3) Catadioptric camera video dataset for vehicle classification
Set 1: contains 124 videos for cars (in 5 parts, ~270 MB each).
Set 2: contains 104 videos for vans (minibus) (in 4 parts, ~290 MB each).
Set 3: contains 49 videos for motorcycles (in 2 parts, ~270 MB each).
For each video the following data is included in the zip files: i) the video itself (avi format), ii) the foreground mask of each frame obtained with background subtraction, iii) the foreground mask of each frame containing the vehicle, iv) annotated area covered by the vehicle (to be used as groundtruth) while vehicle is at the closest point to the camera.
Related publication: Karaimer, H.C. and Bastanlar, Y., Detection and Classification of Vehicles from Omnidirectional Videos using Temporal Average of Silhouettes, Int. Conference on Computer Vision Theory and Applications (2015).
Dataset 1 (37 MB) contains 30 omnidirectional images to detect (standing) humans (66 annotated instances) and 50 omnidirectional images to detect (side-view) cars (65 annotated instances).
4) Omnidirectional and panoramic image dataset (with annotations) to be used for human and car detection
Dataset also contains panoramic images converted from the omnidirectional ones.
Annotations are provided in three sets: i) rectangular bounding boxes sliding and rotating around image center for omnidirectional images, ii) proposed (dough-nut slice) annotations for omnidirectional images, iii) standard (up-right) bounding box annotations for panoramic images.
Dataset 2 (5 MB) contains synthetic catadioptric omnidirectional images which are formed by projecting perspective images to a 'defined' omnidirectional camera. One set projects 210 perspective images from INRIA person dataset, the other one projects 466 car side-views from UIUC and Darmstadt perspective image datasets.
Related publication: Cinaroglu, I. and Bastanlar, Y. (2014), A Direct Approach for Human Detection with Catadioptric Omnidirectional Cameras, IEEE Conference on Signal Processing and Communications Applications (SIU) 2014.
Dataset (5MB) contains i) 25 para-catadioptric images, ii) 50 cylindrical panoramic images obtained from the catadioptric images (25 original and 25 mirrored), annotations for cars in those images, iii) 50 spherical panoramic images obtained from the catadioptric images, annotations for cars in those images.
5) Panoramic image dataset (with annotations) to be used for car detection
Related publication: Karaimer, H.C. and Bastanlar, Y. (2014), Car Detection with Omnidirectional Cameras Using Haar-like Features and Cascaded Boosting (in Turkish), IEEE Conference on Signal Processing and Communications Applications (SIU) 2014.
6) Image datasets to be used in studies on hybrid structure-from-motion and omnidirectional camera calibration
Hybrid Set 1: A perspective and a catadioptric omnidirectional camera (together with camera parameters and calibration images).
Hybrid Set 2: An omnidirectional camera and some frames (approx. 1/sec.) from a perspective footage (with camera parameters and calibration images).
Hybrid Set 3: A perspective, a fisheye and a para-catadioptric omnidirectional camera (together with camera parameters and calibration images).
Hybrid Set 4: A perspective and a catadioptric omnidirectional camera (together with camera parameters and calibration images).
Hyperbolic Calibration Set: A set of calibration images for a catadioptric camera with an hyperbolic mirror (NeoVision H3S).
Note: Some of the above sets are available in bitmap format (on request).
Related publication: Bastanlar et al.(2012), Multi-view Structure-from-Motion for Hybrid Camera Scenarios.