I have a video from a fixed (stationary) camera. Sometimes there are slight movements in the frames (e.g. tree moving a bit in the wind). Other times, some might walk into the view of the camera, a bird might fly past, etc.

I could build a classifier to detect birds and people... but I don't know what will be picked up on camera. I am aware of models such as imageNet and YOLO, but I don't want to make assumptions (color, shape, size, type, etc.) about what might appear in the frames.

As such, I am looking for a way to detect arbitrary objects (i.e. anything moving relative to the rest of the image) in the video and track them. Classification can happen later.

What approaches exit for this problem? I will be writing in Python.

I have a video from a fixed (stationary) camera. Sometimes there are slight movements in the frames (e.g. tree moving a bit in the wind). Other times, some might walk into the view of the camera, a bird might fly past, etc.

I could build a classifier to detect birds and people... but I don't know what will be picked up on camera. I am aware of models such as imageNet and YOLO, but I don't want to make assumptions (color, shape, size, type, etc.) about what might appear in the frames.

As such, I am looking for a way to detect arbitrary objects (i.e. anything moving relative to the rest of the image) in the video and track them. Classification can happen later.

What approaches exist for this problem? I will be writing in Python.

I have a video from a fixed (stationary) camera. Sometimes there are slight movements in the frames (e.g. tree moving a bit in the wind). Other times, some might walk into the view of the camera, a bird might fly past, etc.

I could build a classifier to detect birds and people... but I don't know what will be picked up on camera. I am aware of models such as imageNet and YOLO, but I don't want to make assumptions about what might appear in the frames.

As such, I am looking for a way to detect arbitrary objects in the video and track them. Classification can happen later.

What approaches exit for this problem? I will be writing in Python.

I have a video from a fixed (stationary) camera. Sometimes there are slight movements in the frames (e.g. tree moving a bit in the wind). Other times, some might walk into the view of the camera, a bird might fly past, etc.

I could build a classifier to detect birds and people... but I don't know what will be picked up on camera. I am aware of models such as imageNet and YOLO, but I don't want to make assumptions (color, shape, size, type, etc.) about what might appear in the frames.

As such, I am looking for a way to detect arbitrary objects (i.e. anything moving relative to the rest of the image) in the video and track them. Classification can happen later.

What approaches exit for this problem? I will be writing in Python.