Abstract
In object detection, detecting an object with 100 pixels is substantially different from detecting an object with 10 pixels. Many object detection algorithms assume that the pedestrian scale is fixed during detection, such as the DPM detector. However, detectors often give rise to different detection effects under the circumstance of different scales. If a detector is used to perform pedestrian detection in different scales, the accuracy of pedestrian detection could be improved. A multi-resolution DPM pedestrian detection algorithm is proposed in this paper. During the stage of model training, a resolution factor is added to a set of hidden variables of a latent SVM model. Then, in the stage of detection, a standard DPM model is used for the high resolution objects and a rigid template is adopted in case of the low resolution objects. In our experiments, we find that in case of low resolution objects the detection accuracy of a standard DPM model is lower than that of a rigid template. In Caltech, the omission ratio of a multi-resolution DPM detector is 52% with 1 false positive per image (1FPPI); and the omission ratio rises to 59% (1FPPI) as far as a standard DPM detector is concerned. In the large-scale sample set of Caltech, the omission ratios given by the multi-resolution and the standard DPM detectors are 18% (1FPPI) and 26% (1FPPI), respectively.
Highlights
Pedestrian detection has been a hotspot in computer vision research [1]
In the stage of detection, a standard deformable part model (DPM) model is used for the high resolution objects and a rigid template is adopted in case of the low resolution objects
In Caltech, the omission ratio of a multi-resolution DPM detector is 52% with 1 false positive per image (1FPPI); and the omission ratio rises to 59% (1FPPI) as far as a standard DPM detector is concerned
Summary
Pedestrian detection has been a hotspot in computer vision research [1]. The corresponding detection algorithm has been developed towards high precision and instantaneity [2] [3]. Pedestrians contain rich information in the case of high resolution [6], and it is more likely for them to be detected. Even if they are locally overlapped, many algorithms have the capability to detect these targets [7]. In the case low resolution, the pedestrians which contain a small amount of information cannot be detected . A detection algorithm has a much better detection result for the high resolution pedestrians than that for the low resolution pedestrians. We propose a multi-resolution DPM pedestrian detection algorithm, which takes advantage of the standard DPM framework in training the pedestrian with the resolution factor as a hidden variable.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
