fly_matched_filter — FLYVISION `selfmotion` op

• 数据种类:table → matrix

• 调用: import fullseye as fs; fs.ledger.fly_matched_filter(lattice, axis=(0.0, 0.0, 1.0), motion='rotation', depth_m=1.0)(要直接调用实现,import flyvision; flyvision.fly_matched_filter(lattice, axis=(0.0, 0.0, 1.0), motion='rotation', depth_m=1.0);从台账取用则 opsflyvision.get("fly_matched_filter"))

用法

> 该算子的说明尚无译文,以下照原文给出。

The flow field one unit of self-motion writes on the eye — the template a

wide-field neuron is matched to.

Krapp & Hengstenberg measured the local motion sensitivity of single

lobula-plate tangential cells across the whole visual field and found a

structured vector field, one that looks like the optic flow of a particular

rotation of the fly (*Nature* 384:463, 1996). Reading self-motion out of such

a cell is then a matched filter (Franz & Krapp, *Biol. Cybern.* 83:185, 2000):

correlate the measured flow against the template of the motion you are asking

about. This op builds the template, for the isotropic world model — every

point at the same distance — which is the case in which the rotation template

is exactly the geometry and nothing is assumed about the scene:

• `motion="rotation"`: one radian per second about the unit vector *axis*

moves the viewing direction `d at -axis x d`, which is already

tangent to the sphere. Its length is `sin` of the angle between the axis

and the line of sight, so the template is zero on the axis itself.

• `motion="translation"`: one metre per second along *axis*, with every

point at *depth_m* metres, moves it at `-(v - (v.d) d)/Z`. The depth is

an input, not a measurement — translation flow and distance are the same

unknown and no eye can separate them from one frame pair.

lattice: a :func:fly_hex_lattice result. axis: the rotation axis or

translation direction in body coordinates (x forward, y left, z up); it is

normalised, and a zero vector is refused. depth_m: the uniform distance,

`motion="translation"` only.

Returns `(n, 2)` float64 — the azimuth and elevation components of the flow

at each ommatidium, in radians per second, the same layout

:func:fly_flow_from_directions returns.

Ground truth: for a rotation, `|f| = sin(angle(axis, d))` exactly, so it is

0 where the line of sight is along the axis and 1 where it is perpendicular;

and the flow is perpendicular to both the axis and the line of sight. For a

translation, `|f| = sin(angle)/depth` and the flow points away from the

direction of travel (the focus of expansion is where the template vanishes).

Raises `ValueError`: a malformed *lattice*, an *axis* that is not three

finite numbers or is zero-length, an unknown *motion*, and a non-positive

*depth_m*.

详细使用指南

• fly_vision 族使用指南

参考(示例数据・文献)

• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。

• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。

• 算法的正典(作者・年份)与用途见上面的族使用指南。

可运行的示例(实际调用该算子并已验证的样例)

• poc_fly_optomotor_steering — py -3.11 examples/poc_fly_optomotor_steering.py

类型可衔接的下一个算子(可接受 `matrix` 作为输入)

fly_lamina_filter · fly_onoff_split · fly_t4t5_field · fly_flow_from_directions · fly_egomotion_from_flow · fly_hs_readout

同类别(`selfmotion`)

fly_egomotion_from_flow · fly_eye_merge

*Provenance: flyvision.py — FLYVISION 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*

fly_matched_filter — FLYVISION selfmotion op

用法