BATTLECAM™: A Dynamic Camera System for Real-Time

Strategy Games

Yangli Hector YeeGraphics Programmer, Petroglyph

hector@petroglyphgames.com

Elie ArabianLead Artist, Petroglyph

elie@petroglyphgames.com

Overview Background Theory Implementation Hacks Cinematic Shots Question & Answers

Background – History RTS Bird’s Eye (Dune 2) First Person (Dungeon Keeper) Scripted Actor & Camera (Warcraft

3) Unscripted Actor, Unscripted

Camera (Star Wars – Empire at War)

Background - Problem Make a ‘movie’ from an RTS battle

Actors can move during shot Actors can die during shot Players can move actors Objects can move into camera

Background - Solution Pick most interesting object Construct shot Play shot Fallback on death Pick next object Hijack existing camera scripting

Theory – Visual Attention How to pick ‘interesting object’ Bottom Up: Stimulus

Intensity (black on white) Motion (moving stuff) Color (red on green) Orientation (circle in stripes)

Top Down: Goals Game Objectives Current User Selection

Theory – Bottom Up Attn.Image

OrientationColor SpatialFrequencyIntensity Motion

Feature Maps

OrientationColor SpatialFrequencyIntensity Motion

Conspicuity Maps

Saliency Map

Reference : Itti L, Koch C. “A Saliency-Based Search Mechanism for Overt and Covert Shifts of Visual Attention.” Vision Research, pp. 263, Vol 40(10 - 12), 2000

Center Surround Mechanism

Lateral Inhibition

IntensityFeature Maps

IntensityConspicuity Maps

Lateral InhibitionOne signal vs similar signals

Lateral InhibitionPurpose : Promote areas with

significantly conspicuous features while suppressing those that are non-conspicuous.

N(A) N(B) N(C)A B C

(Before Inhibition) (After Inhibition)

Implementation Game Logic Driven

Images too expensive No screen space stuff Access to game logic info

Implementation – Data Game logic data (stimulus)

Size Attack power Location Health

Game logic data (goal driven) Current selection Visibility

Computing Saliency E.g. Saliency_Speed for object(i)

Saliency_speed(i) = (speed(i) – min_speed)/ (max_speed – min_speed)

Normalized 0 to 1Three Normalization modes

Large is importantSmall is imporantCloseness to mean is important

Normalization Modes Large is important

Saliency_val(i) = (val(i) – min_val) / (max_val – min_val)

Small is important Saliency_val(i) = 1 – (val(i) – min_val) / (max_val

– min_val) Close to mean is important

Saliency_val(i) = 1 – (val(i) – avg_val) / (max_val – min_val)

Normalization settings Large is important

Size Attack power Targets Speed

Small is important Health

Close to mean is important X, Y coordinate

Lateral Inhibition Conspicuity value = saliency_val *

(max_saliency_val – min_saliency_val)

Signals with great difference between max and min get boosted

N(A) N(B) N(C)A B C

Importance Importance (i) = Sum of conspicuity_vals * weights Weight values

Size 1.0 Power 1.0 X 0.5 Y 0.5 Health 1.0 Targets 1.5 Speed 1.0

Sort list by importance

Summary Compute normalized saliency Perform lateral inhibition Weighted sum Sort by importance

Picking interesting object Pick current selected Pick current object’s target 50% of

the time Make interesting object list From list pick top 5 randomly. Reject

if it was same type as the previous object looked at.

Constructing Cinematics Local Space

Transform object space cinematic into world Local Space without rotation frame

Use translation only World space using reference objects

For artist driven cinematic constructed in world space

Transform to local space

Local Space Cameras

Flyby camera shot

Circle camera shot

Chase camera shot

Hardpoint camera shot

Frigate/Target camera shot

Demo & Q&A Thanks to

Jim Richmond for camera system Kevin Prangley for illustrations Petroglyph staff for support

Contact Info Hector at petroglyphgames dot com