Colour vision brings clarity to shadows.

نویسندگان

  • Frederick A A Kingdom
  • Catherine Beauce
  • Lyndsay Hunter
چکیده

We have revealed a new role for colour vision in visual scene analysis: colour vision facilitates shadow identification. Shadows are important features of the visual scene, providing information about the shape, depth, and movement of objects. To be useful for perception, however, shadows must be distinguished from other types of luminance variation, principally the variation in object reflectance. A potential cue for distinguishing shadows from reflectance variations is colour, since chromatic changes typically occur at object but not shadow boundaries. We tested whether colour cues were exploited by the visual system for shadow identification, by comparing the ability of human test subjects to identify simulated shadows on chromatically variegated versus achromatically variegated backgrounds with identical luminance compositions. Performance was superior with the chromatically variegated backgrounds. Furthermore, introducing random colour contrast across the shadow boundaries degraded their identification. These findings demonstrate that the visual system exploits inbuilt assumptions about the relationships between colour and luminance in the natural visual world.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Markov Random Field Framework for Finding Shadows in a Single Colour Image

Many computer vision algorithms, such as segmentation, tracking, and stereo registration, are confounded by shadows in images. Hence finding shadows in colour images is an important research issue. As opposed to the majority of techniques, which either need a sequence of images or require geometric information on images, this paper proposes an illuminant discontinuity measure by which shadow ed...

متن کامل

Chromatic shadow detection and tracking for moving foreground segmentation

Advanced segmentation techniques in the surveillance domain deal with shadows to avoid distortions when detecting moving objects. Most approaches for shadow detection are still typically restricted to penumbra shadows and cannot cope well with umbra shadows. Consequently, umbra shadow regions are usually detected as part of moving objects, thus affecting the performance of the final detection. ...

متن کامل

Removing car shadows in video images using entropy and Euclidean distance features

Detecting car motion in video frames is one of the key subjects in computer vision society. In recent years, different approaches have been proposed to address this issue. One of the main challenges of developed image processing systems for car detection is their shadows. Car shadows change the appearance of them in a way that they might seem stitched to other neighboring cars. This study aims ...

متن کامل

Performance evaluation of local colour invariants

In this paper, we compare local colour descriptors to grey-value descriptors. We adopt the evaluation framework of Mikolayzcyk and Schmid. We modify the framework in several ways. We decompose the evaluation framework to the level of local grey-value invariants on which common region descriptors are based. We compare the discriminative power and invariance of grey-value invariants to that of co...

متن کامل

Automatic and accurate shadow detection from (potentially) a single image using near-infrared information

Shadows, due to their prevalence in natural images, are a long studied phenomenon in digital photography and computer vision. Indeed, their presence can be a hindrance for a number of algorithms; accurate detection (and sometimes subsequent removal) of shadows in images is thus of paramount importance. In this paper, we present a method to detect shadows in a fast and accurate manner. To do so,...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Perception

دوره 33 8  شماره 

صفحات  -

تاریخ انتشار 2004