diff --git a/mediapipe/tasks/web/vision/core/types.d.ts b/mediapipe/tasks/web/vision/core/types.d.ts
index c985a9f36..64d67bc30 100644
--- a/mediapipe/tasks/web/vision/core/types.d.ts
+++ b/mediapipe/tasks/web/vision/core/types.d.ts
@@ -19,7 +19,10 @@ import {NormalizedKeypoint} from '../../../../tasks/web/components/containers/ke
 /** A Region-Of-Interest (ROI) to represent a region within an image. */
 export declare interface RegionOfInterest {
   /** The ROI in keypoint format. */
-  keypoint: NormalizedKeypoint;
+  keypoint?: NormalizedKeypoint;
+
+  /** The ROI as scribbles over the object that the user wants to segment. */
+  scribble?: NormalizedKeypoint[];
 }
 
 /** A connection between two landmarks. */
diff --git a/mediapipe/tasks/web/vision/image_segmenter/image_segmenter_test.ts b/mediapipe/tasks/web/vision/image_segmenter/image_segmenter_test.ts
index c1ccd7997..8c8767ec7 100644
--- a/mediapipe/tasks/web/vision/image_segmenter/image_segmenter_test.ts
+++ b/mediapipe/tasks/web/vision/image_segmenter/image_segmenter_test.ts
@@ -263,7 +263,7 @@ describe('ImageSegmenter', () => {
     });
   });
 
-  it('invokes listener once masks are avaiblae', async () => {
+  it('invokes listener once masks are available', async () => {
     const categoryMask = new Uint8ClampedArray([1]);
     const confidenceMask = new Float32Array([0.0]);
     let listenerCalled = false;
diff --git a/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter.ts b/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter.ts
index 67d6ec3f6..60ec9e1c5 100644
--- a/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter.ts
+++ b/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter.ts
@@ -338,16 +338,31 @@ export class InteractiveSegmenter extends VisionTaskRunner {
     const renderData = new RenderDataProto();
 
     const renderAnnotation = new RenderAnnotationProto();
-
     const color = new ColorProto();
     color.setR(255);
     renderAnnotation.setColor(color);
 
-    const point = new RenderAnnotationProto.Point();
-    point.setNormalized(true);
-    point.setX(roi.keypoint.x);
-    point.setY(roi.keypoint.y);
-    renderAnnotation.setPoint(point);
+    if (roi.keypoint && roi.scribble) {
+      throw new Error('Cannot provide both keypoint and scribble.');
+    } else if (roi.keypoint) {
+      const point = new RenderAnnotationProto.Point();
+      point.setNormalized(true);
+      point.setX(roi.keypoint.x);
+      point.setY(roi.keypoint.y);
+      renderAnnotation.setPoint(point);
+    } else if (roi.scribble) {
+      const scribble = new RenderAnnotationProto.Scribble();
+      for (const coord of roi.scribble) {
+        const point = new RenderAnnotationProto.Point();
+        point.setNormalized(true);
+        point.setX(coord.x);
+        point.setY(coord.y);
+        scribble.addPoint(point);
+      }
+      renderAnnotation.setScribble(scribble);
+    } else {
+      throw new Error('Must provide either a keypoint or a scribble.');
+    }
 
     renderData.addRenderAnnotations(renderAnnotation);
 
diff --git a/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter_test.ts b/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter_test.ts
index 84ecde00b..a361af5a1 100644
--- a/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter_test.ts
+++ b/mediapipe/tasks/web/vision/interactive_segmenter/interactive_segmenter_test.ts
@@ -26,10 +26,14 @@ import {WasmImage} from '../../../../web/graph_runner/graph_runner_image_lib';
 import {InteractiveSegmenter, RegionOfInterest} from './interactive_segmenter';
 
 
-const ROI: RegionOfInterest = {
+const KEYPOINT: RegionOfInterest = {
   keypoint: {x: 0.1, y: 0.2}
 };
 
+const SCRIBBLE: RegionOfInterest = {
+  scribble: [{x: 0.1, y: 0.2}, {x: 0.3, y: 0.4}]
+};
+
 class InteractiveSegmenterFake extends InteractiveSegmenter implements
     MediapipeTasksFake {
   calculatorName =
@@ -134,22 +138,42 @@ describe('InteractiveSegmenter', () => {
   it('doesn\'t support region of interest', () => {
     expect(() => {
       interactiveSegmenter.segment(
-          {} as HTMLImageElement, ROI,
+          {} as HTMLImageElement, KEYPOINT,
           {regionOfInterest: {left: 0, right: 0, top: 0, bottom: 0}}, () => {});
     }).toThrowError('This task doesn\'t support region-of-interest.');
   });
 
-  it('sends region-of-interest', (done) => {
+  it('sends region-of-interest with keypoint', (done) => {
     interactiveSegmenter.fakeWasmModule._waitUntilIdle.and.callFake(() => {
       expect(interactiveSegmenter.lastRoi).toBeDefined();
       expect(interactiveSegmenter.lastRoi!.toObject().renderAnnotationsList![0])
           .toEqual(jasmine.objectContaining({
             color: {r: 255, b: undefined, g: undefined},
+            point: {x: 0.1, y: 0.2, normalized: true},
           }));
       done();
     });
 
-    interactiveSegmenter.segment({} as HTMLImageElement, ROI, () => {});
+    interactiveSegmenter.segment({} as HTMLImageElement, KEYPOINT, () => {});
+  });
+
+  it('sends region-of-interest with scribble', (done) => {
+    interactiveSegmenter.fakeWasmModule._waitUntilIdle.and.callFake(() => {
+      expect(interactiveSegmenter.lastRoi).toBeDefined();
+      expect(interactiveSegmenter.lastRoi!.toObject().renderAnnotationsList![0])
+          .toEqual(jasmine.objectContaining({
+            color: {r: 255, b: undefined, g: undefined},
+            scribble: {
+              pointList: [
+                {x: 0.1, y: 0.2, normalized: true},
+                {x: 0.3, y: 0.4, normalized: true}
+              ]
+            },
+          }));
+      done();
+    });
+
+    interactiveSegmenter.segment({} as HTMLImageElement, SCRIBBLE, () => {});
   });
 
   it('supports category mask', async () => {
@@ -168,7 +192,7 @@ describe('InteractiveSegmenter', () => {
 
     // Invoke the image segmenter
     return new Promise<void>(resolve => {
-      interactiveSegmenter.segment({} as HTMLImageElement, ROI, result => {
+      interactiveSegmenter.segment({} as HTMLImageElement, KEYPOINT, result => {
         expect(interactiveSegmenter.fakeWasmModule._waitUntilIdle)
             .toHaveBeenCalled();
         expect(result.categoryMask).toBeInstanceOf(MPImage);
@@ -199,7 +223,7 @@ describe('InteractiveSegmenter', () => {
     });
     return new Promise<void>(resolve => {
       // Invoke the image segmenter
-      interactiveSegmenter.segment({} as HTMLImageElement, ROI, result => {
+      interactiveSegmenter.segment({} as HTMLImageElement, KEYPOINT, result => {
         expect(interactiveSegmenter.fakeWasmModule._waitUntilIdle)
             .toHaveBeenCalled();
         expect(result.categoryMask).not.toBeDefined();
@@ -239,7 +263,7 @@ describe('InteractiveSegmenter', () => {
     return new Promise<void>(resolve => {
       // Invoke the image segmenter
       interactiveSegmenter.segment(
-          {} as HTMLImageElement, ROI, result => {
+          {} as HTMLImageElement, KEYPOINT, result => {
             expect(interactiveSegmenter.fakeWasmModule._waitUntilIdle)
                 .toHaveBeenCalled();
             expect(result.categoryMask).toBeInstanceOf(MPImage);
@@ -276,7 +300,7 @@ describe('InteractiveSegmenter', () => {
     });
 
     return new Promise<void>(resolve => {
-      interactiveSegmenter.segment({} as HTMLImageElement, ROI, () => {
+      interactiveSegmenter.segment({} as HTMLImageElement, KEYPOINT, () => {
         listenerCalled = true;
         resolve();
       });
diff --git a/mediapipe/tasks/web/vision/pose_landmarker/pose_landmarker_test.ts b/mediapipe/tasks/web/vision/pose_landmarker/pose_landmarker_test.ts
index c97b0d7b0..907cb16b3 100644
--- a/mediapipe/tasks/web/vision/pose_landmarker/pose_landmarker_test.ts
+++ b/mediapipe/tasks/web/vision/pose_landmarker/pose_landmarker_test.ts
@@ -298,7 +298,7 @@ describe('PoseLandmarker', () => {
     });
   });
 
-  it('invokes listener once masks are avaiblae', (done) => {
+  it('invokes listener once masks are available', (done) => {
     const landmarksProto = [createLandmarks().serializeBinary()];
     const worldLandmarksProto = [createWorldLandmarks().serializeBinary()];
     const masks = [