CVC-02: Onboard Sequence Pedestrian Dataset 2

Date:21 Apr, 2016

CVC-02: Onboard Sequence Pedestrian Dataset 2

    CVC09_FIR_Crops

    CVC-02 consists of three subsets, each one focused on a different task of pedestrian detection: candidate generation, classification and system evaluation. The imagery has been recorded in urban scenarios around Barcelona (Spain), using a Bumblebee color stereo camera with resolution 640×480 pixels and 6mm focal length. The annotated pedestrians are in the range from 0 to 50 m from the camera, which corresponds to a smallest pedestrian of 12×24 pixels. The main features of each subset are the following:

    • CVC-02-CG (Candidate Generation): 100 frames in color, depth and 3D points information.
    • CVC-02-Classification: training (1016 cropped positives and mirrors, 7650 cropped negatives and pedestrian-free images), testing set (window-based, with 570 cropped positives and mirrors, 7500 cropped negatives and pedestrian-free images) and testing set (image-based, with 250 frames containing 587 annotated pedestrians).
    • CVC-02-System: 15 sequences of 4364 frames, 7983 pedestrian annotations.

    All the images are provided in lossless PNG format, both in color and depth versions, and in their original size and 64×128 pixels rescaled. Regarding the annotations, we label them as obligatory or optional (very young children, significantly occluded or partially out of the image).

    Disclaimer: Please, read the terms of use before downloading the dataset.
    When using this dataset in your research, we will be happy if you cite us
    D. Gerónimo, A.D. Sappa, D. Ponsa and A.M. López. 2D-3D Based on-board pedestrian detection system. In Computer Vision and Image Understanding (Special Issue on Intelligent Vision Systems) (CVIU) Vol. 114, Num. 5, pp. 583-595. May 2010.

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    CVC-02: Candidate Generation
    CVC-02: Classification
    CVC-02: System

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