Tag Archives: human detection

Human detection and Pose Estimation with Deep Learning for Sport Analysis

Pose estimation and tracking human is one the key step in sports analysis. Here is in this work I used openpose for analysis of player in a Bundesliga game HSV Hamburg vs Bayer München. Warning: the video might be disturbing for HSV fans 🙂

 

Original Video

Analyzed Video

Original Video

Analyzed Video

Original Video

Analyzed Video

Original Video

Analyzed Video

Vaganova_Ballet_Academy from Behnam Asadi on Vimeo.

 

Original Video

Analyzed Video

 

 

Thiem_Zverev from Behnam Asadi on Vimeo.

Human detection on mobile camera using HOG and tracking them using Kalman filter

This is the part I of the work that I did for my master thesis (part II). In this work first, I computed HOG (Histogram of oriented gradients) on my images and then sent the computed histogram to a linear SVM (support vector machine). The SVM was trained with human and non-human images. The output of the classifier was abounding box if there was any human in the image.

Feature extraction and object detection in HOG, Tiling the detection window in an overlapping grid of HOG descriptors and then using a SVM based window classifier gives the human detection chain. Image acquired from [1].

Overview of HOG, The detector window is tiled with a grid of overlapping blocks, Each block contains a grid of spatial cells. For each cell, the weighted vote of image gradients in orientation histogram is accumulated. These 31 are locally normalized and collected into one big feature vector. Images acquired from [2].

In the next, I used Kalman filter to track the detected human. To check the accuracy of my work, I created a ground truth based on the color tracker. You can read and download a similar one on my website here.

 

The bounding box shows the Kalman filter prediction while the letter 1 or 2 indicate the human detection by HOG and letter R and Y are locations of the player detected by the color tracker.

All text and images in this article are taken from my master thesis or respective publications, the full document can be downloaded here.

[1] N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 886 –893 vol. 1, June 2005. doi: 10.1109/CVPR.2005.177.

[2] N. Dalal and B . Triggs. Histograms of oriented gradients for human detection., 2005.